Clinical Validation of a Computer-Aided Diagnosis (CAD) System Utilizing Artificial Intelligence Algorithms for Continuous and Remote Monitoring of Patient Condition Severity in an Objective and Stable Manner
Conditions: Skin Diseases, Skin Condition
Sponsor: AI Labs Group S.L

 
 
Study title 
Pilot study for the clinical validation of a Computer 
Aided 
Diagnosis 
(CAD) 
system 
with 
artificial 
intelligence algorithms for a continuous and remote 
monitoring of the severity of the patient's condition in 
an objective and stable way. 
 
 
 
Protocol code: LEGIT_COVIDX_EVCDAO_2022 
Protocol version: Version 2.0, date March 03rd, 2022 
 
 
 
 
Confidentiality Statement 
This document contains confidential information that cannot be disclosed to persons outside 
the conduct of this study, other than the participating investigators, persons associated with the 
conduct and coordination of the study, regulatory entities, or members of Ethics Committees. 
 
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PROTOCOL SIGNATURE PAGE 
Protocol code: LEGIT_COVIDX_EVCDAO_2022 
Product under investigation: Legit.Health Plus 
I have read this protocol and agree that it contains all the details necessary for the conduct 
of the study as described herein. I will conduct this protocol in the manner provided herein, 
and will make every reasonable effort to complete the study within the time frame 
designated for it. 
I will provide copies of the protocol and all necessary information to personnel participating 
in the study who will be under my supervision. I will discuss and clarify, to the extent 
possible, this material with them to ensure that they have complete information about the 
conduct of the study. 
I will provide information about the protocol to the Clinical Research Ethics Committee 
(IRB) subject to the following conditions: the contents of this protocol may not be used in 
any other study and may not be disclosed to any other person or entity without the prior 
written consent of the Principal Investigator. The above shall not apply to disclosure 
required by government regulations or laws; however, the study coordinator must be 
notified of such disclosure immediately. 
I understand that I may terminate the study or suspend recruitment at any time if 
necessary to protect the interests of the study subjects. The investigator also has the right 
to terminate the study with or without cause at any time. 
I hereby agree to conduct this study in accordance with all stipulations of the protocol and 
the Declaration of Helsinki. 
 
Personnel Signature: Principal Investigator 
Date 
Signature 
 
 
 
 
 
 
 
​
​
​
​
 
 
 
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INDEX 
 
1. GENERAL INFORMATION​
5 
1.1 Study identification​
5 
1.2 Sponsor​
5 
1.3 Principal investigator/Colaborators and investigational site​
5 
2. INTRODUCTION AND JUSTIFICATION​
7 
3. STUDY TYPE AND DESIGN​
9 
4. OBJECTIVES​
9 
4.1 Hypothesis​
9 
4.2 Main objective​
9 
4.3 Secondary objectives​
9 
5. MATERIAL AND METHODS​
10 
5.1 Study period​
10 
5.2 Study design and development​
10 
5.2.1 Patient selection and recruitment visit​
10 
5.2.2 Procedures to be performed by the patient at home​
11 
5.2.2.1 Completion of questionnaires​
11 
5.2.2.2 Taking photographs​
11 
5.2.3 Follow-up visits​
12 
5.2.4 Advice from the Legit.Health team on the study​
12 
6. STUDY VARIABLES​
12 
6.1 Main variable​
12 
6.2 Secondary variables​
13 
7. PARTICIPANTS​
13 
7.1 Study population​
13 
7.2 Inclusion Criteria​
13 
7.3 Exclusion Criteria​
14 
8. SAMPLE SIZE​
14 
9. RESULTS ANALYSIS​
14 
10. ETHICAL CONSIDERATIONS​
15 
11. PRODUCT DESCRIPTION​
15 
11.1 Diagnosis​
16 
11.2 Follow-up​
16 
12. SAFETY​
18 
13. DATA COLLECTION AND MANAGEMENT​
18 
13.1 Source Data Identification​
18 
13.2 Data quality assurance​
18 
13.3 Data management​
18 
14. STUDY LIMITATIONS​
20 
 
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15. ANNEXES​
21 
ANNEX I. Clinical Utility Questionnaire (CUS)​
21 
ANNEX II. Patient Satisfaction Questionnaire​
24 
ANNEX III. System Usability Scale - SUS​
26 
ANNEX IV. Dermatology Life Quality Index  (DLQI - Dermatology Life Quality Index)​ 28 
ANNEX V. Data collection notebook​
30 
ANNEX VII. EC Declaration of Conformity​
30 
 
 
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1.​ GENERAL INFORMATION 
1.1​
Study identification 
Title: Pilot study for the clinical validation of a Computer Aided Diagnosis (CAD) system 
with artificial intelligence algorithms for a continuous and remote monitoring of the severity 
of the patient's condition in an objective and stable way. 
Protocol code: LEGIT_COVIDX_EVCDAO_2022. 
Study design: Prospective observational analytical study of a longitudinal clinical case 
series. 
Product under investigation: Legit.Health Plus 
Version and date: Version 2.0, date March 03rd, 2022 
1.2​
Sponsor 
Hospital Universitario de Torrejón, AI LABS GROUP, S.L. y Ribera Salud S.A. 
 
1.3​
Principal investigator/Colaborators and investigational site 
Principal investigator 
Dra. Marta Andreu Barasoain 
Servicio de Dermatología 
Hospital Universitario de Torrejón 
C/ Mateo Inurria, s/n (Soto del Henares) 
28850 - Torrejón de Ardoz 
Collaborating investigators 
Servicio de Dermatología del Hospital 
Universitario de Torrejón 
Dra. Leticia Calzado – Jefa Dermatología 
Dra. Elena Sánchez-Largo - Médico 
adjunto Dermatología 
Dr. Javier Alcántara - Médico adjunto 
Dermatología 
Dra. Tania Marusia Capusan - Médico 
adjunto Dermatología  
Dra. Marta Ruano - Médico adjunto 
Dermatología 
 
AI LABS GROUP, S.L (Legit.Health) 
D. Alfonso Medela 
D. Taig Mac Carthy 
Investigational Site:​  
Hospital Universitario de Torrejón 
Servicio de Dermatología 
 
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C/ Mateo Inurria, s/n (Soto del Henares) 
28850 - Torrejón de Ardoz 
 
 
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2.​ INTRODUCTION AND JUSTIFICATION 
The pandemic caused by the new SARS-CoV-2 virus is challenging healthcare systems 
around the world in different ways. The main focus is on the care of people suffering from 
COVID-19. In particular, the care of critically ill patients in hospitals and intensive care 
units has led to bottlenecks in intensive care capacities in some countries.1 
With the isolation measures in mid-March 2020, health authorities ordered hospitals to 
postpone all admissions, surgical procedures and planned interventions until further notice, 
to the extent medically justifiable, not only to free staff and material resources for the 
treatment of patients with COVID-19, but also to minimize transmissions of the COVID-19 
virus between patients and medical staff. Like all other medical disciplines, this also 
affected dermatology departments in their inpatient and outpatient services. U.S. 
dermatologists called dermatology practices "vectors of COVID-19 transmission"2 and 
recommended the immediate suspension of all "non-urgent" consultations1. This, after 
almost two years, has still not been able to regain its usual flow due to the multiple variety 
of virus variants that continue to plague the healthcare situation. 
Because of this, it is necessary to implement an alternative system so that dermatological 
patients can continue to be diagnosed with their respective pathologies even more quickly, 
comfortably and efficiently, and can also have a remote and continuous follow-up of the 
disease, since many people who have a skin pathology end up going to the doctor when 
they need to. This is due to the unbalanced ratio of dermatologists to patients in most 
European countries, including Spain. This fact not only causes pathologies to go 
unnoticed, but also has deadly effects on patients with skin cancer, especially melanoma, 
and causes chronic diseases such as psoriasis, eczema or hidradenitis suppurativa to 
worsen over time, reducing patients' quality of life and increasing the economic impact on 
each patient. This has been further exacerbated during the COVID-19 crisis, as patients 
avoid going to the doctor to reduce exposure to the virus. 
Unfortunately, as of today there are no reliable tools for remote pathology diagnosis and 
activity. Therefore, the activity of the condition can currently only be measured by a 
specialist physician in consultation. 
In addition, the method currently used to quantify, stage or measure the involvement of 
patients in consultation has severe limitations. The most indisputable limitation is the 
inherent difficulty of human beings to quantify parameters in an objective, stable 
and precise manner. In other words, humans have a limited capacity to count lesions, 
2 Kwatra SG, Sweren RJ, Grossberg AL. Dermatology practices as vectors for COVID-19 
transmission: a call for immediate cessation of non-emergent dermatology visits [Internet]. J Am 
Acad Dermatol 2020; 82(5): e179–e180. 
1 Elsner P. (2020). Teledermatology in the times of COVID-19 - a systematic review. Journal der 
Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : 
JDDG, 18(8), 841–845. https://doi.org/10.1111/ddg.14180 
 
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quantify the surface area of a lesion or document the redness of an area, to give a few 
examples. 
This human limitation in the estimation of parameters is also reflected in the effort and 
time required to estimate the degree of involvement of a patient or the stage of the 
pathology. So much so that it ends up being a very unrewarding task and can result in low 
adherence to the protocol or limited use of the tool. 
On the other hand, the measurement systems in which the professional visually estimates 
the impairment try to classify the disease by severity using a reduced number of 
categories, such as: none, mild, moderate and severe. Because of this, the system has a 
very great minimum detectable change, and a very low sensitivity to change. 
In addition to these inherent limitations, in cases where the measurement scales are 
patient-reported, there is the possibility of bias. This is especially true in cases where the 
patient knows that the treatment he or she receives will be determined by the information 
he or she provides. In addition, the medical team lacks the means to ensure that the 
values reported by the patient are accurate, which precludes external verification. 
Fortunately, in recent years there has been an increasing demand to develop 
Computer-Aided Diagnosis (CAD) systems and other systems that facilitate the 
detection 
of 
different 
pathologies through algorithms. CAD systems are an 
interdisciplinary technology that combines artificial intelligence and digital image 
processing. Image processing based on complex pattern recognition systems makes it 
possible for the physician to interpret the information contained in the medical image with 
much less difficulty. Advances in image recognition and artificial intelligence have led to 
innovations in the diagnosis of all types of pathologies. It has been demonstrated that 
through artificial intelligence (AI) algorithms, it is possible to classify photographs of lesions 
with a level of competence comparable to that of a medical expert3 4. 
Therefore, the use of artificial vision applications when collecting information about the 
patient's condition presents a huge advance that not only brings reliability to the 
documentation process but also allows greater precision when measuring visual 
signs and quantifying the severity of the pathology. 
Thanks to the Legit.Health platform, patients can be evaluated from home, thus avoiding 
the risk of contagion among more patients and healthcare professionals, while at the same 
time monitoring chronic patients to prevent them from getting worse. Likewise, for 
example, patients with moles are analyzed to ensure that they are diagnosed as 
premalignant or malignant and treated in time. A solution that empowers patients with a 
4 Haenssle HA, Fink C, Schneiderbauer R, et al; Reader study level-I and level-II Groups. Man 
against machine: diagnostic performance of a deep learning convolutional neural network for 
dermoscopic 
melanoma recognition in comparison to 58 dermatologists., Ann Oncol. 
2018;29(8):1836-1842.  
3 Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep 
neural networks, Nature. 2017; 542(7639): 115-118. 
 
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systematic means to monitor their disease and also empowers medical practice by 
allowing physicians to better assess patients based on a more holistic view of their 
conditions. 
Accordingly, this study aims to clinically validate a novel artificial intelligence tool for 
activity grading in affected patients. 
This innovation has the potential to facilitate medical practice in the treatment of some 
chronic dermatological pathologies and improve the quality of life of patients affected by 
these pathologies. In addition, this technology provides a new measurement tool that 
opens the door to a new field of research into the effectiveness of treatments or the 
analysis of the pathology itself and its subtypes. 
 
3.​ STUDY TYPE AND DESIGN 
This is a prospective observational analytical study of a longitudinal clinical case series. 
4.​ OBJECTIVES 
4.1​
Hypothesis 
The hypothesis guiding this study is that the Legit.Health Plus tool (hereinafter the device) 
with artificial intelligence developed by AI LABS GROUP SL can perform remote 
monitoring of pathology severity in a continuous and objective manner. 
This hypothesis is based on the notion that artificial intelligence introduces several 
significant changes in the monitoring process: 
1.​ Remote monitoring of dermatological pathology severity in a continuous and 
objective manner. 
2.​ Empowerment of the patient with a systematic tool to monitor their own pathology. 
In short, the hypothesis of the study is that Legit.Health Plus is a very useful tool to reduce 
the need for a patient to visit the doctor so often, since it is possible to monitor the 
evolution of the pathology remotely, thus increasing their empowerment, with the 
consequent reduction in the number of face-to-face consultations in hospitals. 
4.2​
Main objective 
The main objective of the present study is to validate that the device, based on artificial 
intelligence and developed by AI LABS GROUP SL, allows to remotely determine the 
evolution of chronic dermatological pathologies in an objective and stable way, reaching a 
score of 8 or higher in the Clinical Utility Questionnaire (CUS). 
4.3​
Secondary objectives 
Secondary objectives include: 
 
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●​ To validate that the device generates reliable pathology tracking. That is, it is a reliable 
system. 
●​ Validate that the device generates patient satisfaction as it can be used remotely. 
●​ Validate that the device contributes to reducing face-to-face consultations. 
5.​ MATERIAL AND METHODS 
5.1​
Study period 
This study estimates a recruitment period of 6 months.  
The total duration of the study is estimated at 12 months, including the time required after 
recruitment of the last subject for closing and editing the database, data analysis, and 
preparation of the final study report. 
The total duration of the study for each participant will be 6 months from the date of 
inclusion. 
5.2​
Study design and development 
Patients who meet the selection criteria will be offered to participate in the study (see 
section "Participants").  
Patients will be recruited at the Dermatology Department of the Hospital Universitario de 
Torrejón. Recruitment will be carried out by the Principal Investigator or those collaborating 
investigators to whom he/she delegates this task. 
5.2.1​ Patient selection and recruitment visit 
The recruitment period will last six (6) months, during which the investigators will enroll 
patients in the study.  
The Principal Investigator and/or the collaborating investigators assigned to this task will 
explain to the patient what his/her participation in the study will consist of by means of the 
Patient Information Sheet. The patient, in turn, will be able to ask all the questions he/she 
considers appropriate in order to clarify all his/her doubts concerning the study. 
If the patient wishes to participate in the study, he/she will sign the Informed Consent Form 
and will be assigned a study code. After signing the informed consent, the data collection 
process begins. 
The Principal Investigator and/or collaborating investigators assigned to this task will 
collect demographic data (age, sex, ...) and data related to the diagnosis, characteristics 
and treatment of the pathology. Once the information has been completed, he/she will 
proceed to explain to the patient the instructions for completing the questionnaire and 
taking photographs in the device, according to the instructions detailed in the "Patient 
Information Guide" (Annex IV), a copy of which will be given to the patient. 
 
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During this first visit, the patient will take the photograph and complete the questionnaire 
associated with the pathology, if any, in the device under the supervision of the research 
team, who will ensure that the patient understands the instructions correctly.  
After this visit, the patient will take the photographs and complete the questionnaires at 
home autonomously and telematically, as described in the following section. 
The device will be provided free of charge to patients and the research team for the 
duration of the study and the patient's participation in the study. 
5.2.2​ Procedures to be performed by the patient at home 
5.2.2.1​
Completion of questionnaires 
Patients will report their pathology autonomously, at home, by completing the 
questionnaires and following the indications of the research team and the "Patient 
Information Guide" (Appendix IV) provided during the screening visit. 
Periodically, the patient will document the status of his pathology by means of the 
questionnaires corresponding to each pathology and the DLQI (Appendix V), which are 
integrated in the device and are filled in, together with the taking of the photograph. 
On a bimonthly basis, the patient will complete the "Patient Satisfaction Questionnaire" 
(Annex II), which asks about general aspects of the user experience. In addition, he/she 
will complete the System Usability Scale (SUS) Questionnaire (Annex III) at the same 
frequency. 
5.2.2.2​
Taking photographs 
In the same act, by filling in the questionnaires through the app, the patients will have to 
take photographs showing the areas affected by the pathology. These photographs will be 
taken with the patient's smartphone, from their homes and autonomously. These 
photographs will be filled in with the periodicity established by the specialist doctor in 
consultation. 
No technical camera requirements will be necessary: the photographs will be taken with 
the camera available on the patient's smartphone. 
In this way, patients will send the photographs to the research team telematically through 
the device, which consists of a web app with the status of a medical device (Annex VII) in 
which both patients and members of the medical team have access credentials. The 
Legit.Health team will not have access to the account or patient information. 
This transfer of information and the storage of the photographs will be in line with the 
European Regulation 2016/679 of 27 April on the protection of natural persons with regard 
to the processing of personal data and the free movement of such data and the Organic 
Law 3/2018 of 5 December on the Protection of Personal Data and guarantee of digital 
rights. 
 
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5.2.3​ Follow-up visits 
The follow-up period will last six months. During this period, patients will have at least two 
follow-up visits, which may be telematic or face-to-face, during the execution of the study. 
The Principal Investigator and/or collaborating investigators will also collect the patient 
satisfaction questionnaire (Annex II) and the System Usability Scale - SUS (Annex III) on a 
bimonthly basis. 
In addition, the Principal Investigator and/or investigators will complete the Clinical Utility 
Questionnaire (CUS) (Appendix I) and the System Usability Scale (SUS) (Appendix III) on 
a bimonthly basis. 
5.2.4​ Advice from the Legit.Health team on the study 
The Legit.Health team will assist the research team in the process of taking the 
photographs and will supervise the labelling of the photographs to ensure that both the 
photographs and the labelling nomenclature meet the technical criteria necessary for 
further analysis. 
Periodically, the Legit.Health team will meet with the researchers and review the data 
collected to ensure that the entire collection procedure is carried out correctly. 
The periodicity of the reviews follows the following logic: 
1.​ The first review will be performed when samples have been collected from 3 
patients.  
2.​ Subsequently, every 5 new patients. 
In case the first review requires any correction, the next evaluation of the next 3 patients 
will be done. 
Review meetings will be held according to the availability of the investigator. 
6.​ STUDY VARIABLES 
6.1​
Main variable 
The primary endpoint aims to determine the validity of the DAO system developed by AI 
LABS GROUP SL to determine that the monitoring of the severity of the pathology is 
performed in a continuous and objective manner. 
For this purpose, clinicians will fill out the Clinical Utility Questionnaire (CUS) (Annex I) 
provided by Legit.Health. 
As explained in the introduction, patient involvement is diagnosed only observationally. For 
this purpose, when the patient uploads a photo, a new possible diagnosis will be 
generated that has to be confirmed by the specialist, in case he/she has not yet assigned a 
pathology. If a pathology has already been assigned, new information on the evolution of 
the pathology will be generated. 
 
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6.2​
Secondary variables 
●​ Demographic data: sex, age, zip code. 
●​ Clinical data: diagnosis, date of diagnosis, and medication the patient is taking. 
●​ Worsening pathology alerts. 
●​ Quality of life: score of the Dermatology Quality of Life Index or DLQI questionnaire 
(Annex V). 
●​ Degree of patient satisfaction using the patient satisfaction questionnaire (Annex II). 
●​ Consultation management indicators: number of face-to-face consultations, number of 
telematic consultations and consultation times. 
●​ Evaluation of the usability of the device by clinicians and patients, using the System 
Usability Scale (SUS) questionnaire (Annex III). 
●​ Use of the application: logins, photographs sent. 
7.​ PARTICIPANTS 
7.1​
Study population 
Patients with any of the chronic dermatologic pathologies specified in the inclusion criteria 
who attended the Dermatology Department of the Hospital Universitario de Torrejón. 
7.2​
Inclusion Criteria 
●​ Patients with any of the following chronic dermatological pathologies. 
o​
Psoriasis 
o​
Urticaria 
o​
Hidrosadenitis suppurativa 
o​
Acne 
o​
Atopic dermatitis 
o​
Vitiligo 
o​
Infantile hemangioma 
o​
Nail pathology 
●​ Patients who have signed the informed consent for the study. 
●​ Patients with written and spoken proficiency in Spanish or English. 
 
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●​ Patients with a smartphone, i.e.: a phone with internet access and integrated 
camera, of any model and technical characteristics. 
7.3​
Exclusion Criteria 
●​ Patients who, according to the investigator's criteria, will not comply with the study 
procedures. 
●​ Patients who were already using the tool under study. 
 
8.​ SAMPLE SIZE 
A total of 160 patients will be recruited in this study. This study is planned as a "proof of 
concept" pilot study in which the sample size has been estimated based on the number of 
patients diagnosed with any of the pathologies defined in the inclusion criteria. During the 
recruitment period of the study, all patients with a diagnosis of a chronic dermatologic 
pathology who meet the selection criteria will be included. The data collected from these 
patients during the study period will be analyzed, and depending on the results obtained it 
will be assessed whether it is necessary to increase the sample size to include more 
patients. 
9.​ RESULTS ANALYSIS 
Each variable will be characterized using frequency distributions for qualitative variables 
and central tendency statistics, such as mean and median and variability statistics such as 
standard deviation (S.D.) or interquartile range, for quantitative variables according to their 
distributional characteristics. 
Between-group and within-group comparisons will be made using parametric tests 
whenever the distributional characteristics of the data allow it. For intergroup comparisons, 
one- and two-factor Analysis of Variance techniques will be used with post-hoc 
comparisons if significant overall differences are detected. To assess intra-group changes, 
Student's t-test for related samples or Analysis of Variance/ANOVA with repeated 
measures will be used if the theoretical assumptions of the model are supported by the 
data. Otherwise, more flexible models (GEE) that allow incorporating different 
autocorrelation structures of the data will be fitted. 
Comparisons between groups with respect to qualitative variables will be carried out by 
means of contingency tables and Fisher's exact or Chi-square tests. The probability of type 
I error will not be adjusted for multiple comparisons. The level of statistical significance in 
the contrasts (alpha) will be 5 percent with bilateral contrasts.  
Comparisons between two continuous variables will be made using Pearson's or 
Spearman's correlation, depending on the distributional characteristics. 
 
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Sensitivity, specificity, positive and negative predictive values (PPV and NPV) and 
likelihood ratios (LR+ and LR-) will be calculated by comparing the results obtained using 
the Legit.Health tool and the paper questionnaire system used as the gold standard. 
Analyses will be performed using appropriate statistical software, SPSS version 23.0 and 
STATA 13.0. Values of p<0.05 will be considered significant. 
10.​
ETHICAL CONSIDERATIONS 
The conduct of the study will conform to international Good Clinical Practice standards, to 
the Declaration of Helsinki in its latest active amendment, and to international and national 
rules and regulations and will not be initiated until approval has been obtained from the 
Vinalopó-Torrevieja Ethics Committee. Any modification of this protocol will be reviewed 
and approved by the Principal Investigator and must be evaluated by the Ethics Committee 
for approval before including subjects in a modified protocol. 
The study will be conducted according to European Regulation 2016/679, of 27 April, on 
the protection of natural persons with regard to the processing of personal data and the 
free movement of such data and Organic Law 3/2018, of 5 December, on the Protection of 
Personal Data and guarantee of digital rights with regard to data processing in which no 
data that allows the personal identification of subjects will be included, the information 
being managed in an encrypted manner. 
Patients will be informed orally and in writing about all the information related to the study 
and adapted to their level of understanding. A copy of the consent form and information 
sheet should be provided to the patient. The investigator should allow the patient the 
necessary time to ask questions about the details of the study. 
Preparation of the informed consent form is the responsibility of the Principal Investigator. 
This form should include all the elements required by the International Conference of 
Harmonization (ICH), current regulatory guidelines, and comply with the Standards of 
Good Clinical Practice (GCP) and ethical principles that originate from the Declaration of 
Helsinki. 
The investigator or the Principal Investigator's designee will keep the original signed 
informed consent form in a secure, restricted access area under the custody of the 
Principal Investigator and will never leave the center and will give a copy of the original 
signed consent form to the patient. 
11.​
PRODUCT DESCRIPTION 
Legit.Health Plus is a digital medical device (Annex VII) that helps dermatologists to 
introduce a detailed and objective follow-up in the skin evaluation process, thanks to the 
automatic analysis of images and the auto-filling of measurement scales. 
 
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Legit.Health is a trademark of the company AI LABS GROUP SL, domiciled in the Basque 
Country. AI LABS GROUP SL specializes in the use of pioneering machine vision 
techniques and deep learning algorithms to develop algorithms for classification and 
severity estimation of visible pathologies, especially in the world of dermatology.  
The device performs two types of algorithmic operations, with enormous medical utility. 
First, the device algorithms are able to diagnose pathologies. Secondly, they are able to 
track the pathology. 
In all cases, the device is a clinical decision support tool, i.e. its purpose is to help doctors 
in the practice of their profession, reducing their workload and the risk of errors, while 
patients feel more supported. However, it is not software that a patient can use without 
medical supervision, but a tool for communication and automation of the relationship 
between the patient and their doctor. 
​
Software Legit.Health images on different devices. 
11.1​
Diagnosis 
Legit.Health Plus's wide range of diagnostic algorithms allows classification of 232 skin 
pathologies. Specifically, the device has focused on providing diagnostics for chronic 
pathologies, because of the burden they place on the healthcare system and the effects on 
patients' quality of life, and on malignant and pre-malignant pathologies, because of the 
danger they pose to the population. 
11.2​
Follow-up 
In addition to diagnosis, the device algorithms are able to quantify, through a photograph, 
visible signs such as erythema or induration of a skin lesion. In addition, Legit.Health has 
developed algorithms capable of performing wheal and lesion counts. On the other hand, 
the algorithms make it possible to determine the surface area affected by a particular 
pathology with high precision. 
 
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These algorithms make it possible to track the evolution of a pathology by periodically 
analyzing the visual information contained in a photograph. This means that patient 
follow-up is largely automated, resulting in a reduction of the clinical workload. 
An example of such tracking algorithms is acne lesion counting. The acne tracking 
algorithm developed by Legit.Health receives a photograph of the patient and returns 
numerical values related, on the one hand, to the number of lesions, and on the other 
hand, to the concentration and density of lesion clusters. This allows an accurate 
monitoring of the evolution of the pathology, with an extremely high minimum detectable 
change, far superior to the system currently used in medical practice. 
Additionally, the algorithm returns the photograph itself with an explanation of what the 
algorithm has done, as can be seen below: 
 
This photograph provides great medical value, as it allows the healthcare professional and 
the patient to understand what the algorithm has done and to quickly detect if the algorithm 
has made any errors. In other words, it increases the explainability of the algorithm. 
In addition, the device collects symptoms that are not visibly noticeable, such as itching, or 
the different domains of quality of life, through convenient digital questionnaires. 
One of the functionalities of the device most valued by physicians is the automatic filling in 
of scales. In essence: Legit.Health's algorithms automatically fill in scales by simply 
looking at images and collecting short questionnaires from patients. In this way, the tool 
automatically completes most measurement scales, such as UAS7, PASI, SCORAD, BSA, 
DLQI and many more. 
All in all, the device helps physicians 
optimize the time available within a practice, 
as doctors can work with the predicted 
diagnostic data and spend more time 
ensuring that the patient understands the 
implications of their disease and the 
importance of adherence to treatment. 
Ultimately, the device gives patients and 
physicians the ability to track changes in 
 
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skin lesions that are often gradual and subtle, and to correlate different symptoms to 
identify triggers or evaluate treatment performance. 
In this way, patients gain a more detailed understanding of symptoms, changes, treatment 
effectiveness and potential triggers. 
12.​
SAFETY 
Subjects enrolled in this study will not be exposed to any procedure that could jeopardize 
their safety.  
No adverse reactions related to the investigational product are expected. 
13.​
DATA COLLECTION AND MANAGEMENT 
13.1​ Source Data Identification 
Source documents are understood to be all the observations or notes recorded on the 
clinical interventions, as well as all the reports and notes necessary for the reconstruction 
and evaluation of the study's data collection notebook. 
Basically, although not exclusively, the source documents are composed of the documents 
and annotations that form part of the patient's Clinical History and the different surveys to 
be collected in the center. 
Whenever possible, the original document should be kept as the source document; 
however, it is acceptable to provide a photocopy as long as it is clear, legible and an exact 
duplicate of the original document. 
13.2​ Data quality assurance 
The Principal Investigator is responsible for reviewing and approving the study protocol 
and its possible modifications in the future, signing the Principal Investigator's 
commitment, guaranteeing that the persons involved in the center will respect the 
confidentiality of patient information and protect personal data, and reviewing and 
approving the final study report. All members of the research team will assess the eligibility 
of the study patients, inform and request written informed consent, collect the source data 
of the study in the clinical record and transfer them to the Data Collection Forms (CRF) 
(Annex VI). 
13.3​ Data management 
The management of the collection and processing of the study data will be carried out 
through the design of a Data Collection Notebook (CRD) (Annex VI), in paper format, in 
 
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which the investigators assigned to this task will enter the source data of each patient 
participating in the study. 
Current legislation will be complied with in terms of data confidentiality protection 
(European Regulation 2016/679, of 27 April, on the protection of natural persons with 
regard to the processing of personal data and the free movement of such data and 
Organic Law 3/2018, of 5 December, on Personal Data Protection and guarantee of digital 
rights). For this purpose, each patient will receive an alphanumeric identification code in 
the study that will not include any data allowing personal identification (coded CRD). The 
Principal Investigator will have an independent list that will allow the connection of the 
identification codes of the patients participating in the study with their clinical and personal 
data. This document will be filed in a secure area with restricted access, under the custody 
of the Principal Investigator and will never leave the center. 
Once the paper CRDs are completed and closed by the Principal Investigator, the data will 
be transferred to a database. 
As in the CRDs, the Database will comply with current legislation in terms of data 
confidentiality protection (European Regulation 2016/679, of 27 April, on the protection of 
natural persons with regard to the processing of personal data and the free movement of 
such data and Organic Law 3/2018, of 5 December, on the Protection of Personal Data 
and guarantee of digital rights) in which no data allowing personal identification of patients 
will be included. 
The transfer of data from the paper CRD to the electronic Database will be carried out 
using the double data entry technique. This will be done by the researchers collaborating 
in the project. 
The data will be managed and tabulated with consistency rules and logical ranges to 
control inconsistencies during data tabulation. A validation process of the clinical data will 
be carried out by running computer filters based on validation rules, which will 
automatically identify missing values or inconsistencies of clinical data according to the 
protocol. Additionally, manual editing and validation will be performed using descriptive 
and exploratory statistical techniques to complement the detection of logical errors and 
inconsistent values. 
The Database will be considered closed upon completion of all Data Management 
processes and satisfactory resolution of discrepancies and errors in the data. Any changes 
in the databases after its closure can only be made after a written agreement between the 
Principal Investigator and the technical coordinators of the project. 
AI LABS GROUP, S.L. (hereinafter Legit.Health) is the owner of the software named 
"Legit.Health Plus". During the period of validity of this study, Legit.Health will grant a 
license to use the Legit.Health Plus device to the research team free of charge. The 
research team will be the administrator of the account created on the Legit.Health platform. 
Both patients and members of the medical team will have login credentials. The 
Legit.Health team will not have access to the account or patient information. 
 
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The Data Controller is the research team. Legit.Health is the Data Processor and is not 
responsible for the processing of the data included in the Software or its users. 
The storage of data and photographs will be in line with the European Regulation 
2016/679 of 27 April on the protection of natural persons with regard to the processing of 
personal data and the free movement of such data and the Organic Law 3/2018 of 5 
December on the Protection of Personal Data and guarantee of digital rights. At the end of 
the study, all information stored in the device will be totally and permanently deleted. 
The Legit.Health platform complies with current legislation on the protection and 
confidentiality of personal data (European Regulation 2016/679 of 27 April on the 
protection of natural persons with regard to the processing of personal data and on the 
free movement of such data and Organic Law 3/2018 of 5 December on the Protection of 
Personal Data and guarantee of digital rights).  Appropriate technical and organizational 
security measures are adopted to ensure the security of personal data and prevent its 
alteration, loss, unauthorized processing or access, given the state of technology, the 
nature of the data and the risks to which they are exposed, whether from human action or 
the natural physical environment. 
14.​
STUDY LIMITATIONS 
The main limitation of machine learning lies in the quantity and quality of the images 
collected. Variability in illumination, color, shape, size and focus are determinants, in 
addition to the number of images per patient. This means that a large variability within the 
same patient and an insufficient number of images to reflect that variability may result in a 
lower accuracy than expected. 
On the other hand, it is worth mentioning that the present study excludes from its 
objectives factors that would play a role in the validation of a new scale for measuring the 
activity of some chronic dermatological pathology from the device, such as the Minimal 
Detectable Change or the inclusion of new parameters, such as the exact number of 
lesions or the diameter of the largest lesion, and focuses on the diagnostic capability of the 
algorithm and the usability advantages of the tool. 
However, it could be expected that a new data collection tool, such as automatic vision 
algorithms, will open the door to the creation of new measurement scales for some chronic 
dermatological pathology, whose use was not feasible in the absence of such a tool - 
either because of the automaticity of data collection, or because of the precision in the 
calculation of parameters such as the number of lesions, the affected surface or the 
redness. 
 
 
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15.​
ANNEXES 
ANNEX I. Clinical Utility Questionnaire (CUS) 
 We want to know your opinion about the usefulness of the Legit.Health application. Please 
answer the following questions: 
1.​ Medical Speciality. Select your speciality. 
Check only one option 
 
Dermatology 
 
Primary health care 
 
Nursery 
 
Auxiliar 
 
 
2.​ Performance. In your opinion, does the Legit. Health application perform as 
expected/anticipated for its intended use? 
Check only one option 
 
Yes 
 
No 
 
 
3.​ Ease of use. In your opinion, please indicate the degree of difficulty in using the 
Legit.Health application. 
(0 = Very difficult; 10 = Very easy): 
Very 
difficult 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
easy 
 
 
 
 
 
 
 
 
 
 
 
 
4.​ Usefulness of the information. In your opinion, indicate the degree of usefulness of 
the information provided by Legit.Health for clinical decision making. 
(0 = No useful; 10= Very useful): 
No 
useful 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
useful 
 
 
 
 
 
 
 
 
 
 
 
 
5.​ Remote consultations. In your opinion, and taking into account that when a patient 
uploads a photo from home and the algorithms process it, it counts as a consultation, 
how much have you been able to reduce the average consultation time per patient? 
Check only one option 
 
I have not reduced time 
 
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Between 1 and 4 minutes 
 
 
Between 4 and 8 minutes 
 
 
More than 8 minutes 
 
6.​ Resource optimization. In your opinion, do you think the Legit.Health application has 
helped you to optimize your time according to the needs of each patient? 
 
Yes 
 
No 
 
7.​ Patient triage. In your opinion, has the patient prioritization option helped you to better 
manage patients with higher clinical requirements? 
(0 = No help; 10= A lot of help: 
No help 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
A lot of 
help 
 
 
 
 
 
 
 
 
 
 
 
 
8.​ Speed. In your opinion, how fast do you find the generation of the report with the 
results of the algorithms? 
(0 = Very slow; 10= Very fast): 
Very 
slow 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
fast 
 
 
 
 
 
 
 
 
 
 
 
 
9.​ Diagnostic support. In your opinion, how efficient is the tool in terms of diagnostic 
support? 
(0 = Very inefficient; 10= Very efficient): 
Very 
inefficie
nt 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
efficient 
 
 
 
 
 
 
 
 
 
 
 
 
10.​Constant monitoring. In your opinion, do you think the Legit.Health application 
contributes to obtaining more information about the patient's condition? 
 
Yes 
 
No 
 
11.​Degree of objectivity. In your opinion, to what degree does the Legit.Health 
application increase objectivity in patient follow-up? 
(0 = A little; 10 = A lot): 
A little 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
A lot 
 
 
 
 
 
 
 
 
 
 
 
 
 
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12.​Overall satisfaction. Indicate the degree of satisfaction with the Legit.Health 
application for remote monitoring of dermatological diseases. 
(0 = Very unsatisfied; 10= Very satisfied): 
Very 
unsatisf
ied 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
satisfie
d 
 
 
 
 
 
 
 
 
 
 
 
 
13.​How likely would you be to recommend this service to another professional? 
(0 =  Surely you would not recommend it; 10= Surely you would recommend it): 
Surely 
you 
would 
not 
recom
mend it 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Surely 
you 
would 
recom
mend it 
 
 
 
 
 
 
 
 
 
 
 
 
14.​Describe in your own words how Legit.Health has helped you manage patients with 
dermatological diseases. 
 
 
 
 
 
 
 
To calculate the CUS score, the contributions of each item must first be summed. The 
contribution of each item will be worth between 0 and 10 for all those questions that 
include a score from 0 to 10. For questions 1, 6 and 10, the contribution will be 0 for no 
and 10 for yes. For question 5, the option I have not reduced time counts as 0, Between 1 
and 4 minutes counts as 4, Between 4 and 8 minutes as 8 and More than 8 minutes as 10. 
The sum of the results is multiplied by 100 and divided by 120 to obtain the overall SUS 
value. The result will be between 0 and 100. 
 
 
 
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ANNEX II. Patient Satisfaction Questionnaire 
We would like to know your opinion about the tools used. Please rate from 0 to 10 the 
following aspects of your experience, following the references: 
1.​ Ease of use: Do you find the App intuitive and easy to use? 
(0 = Very difficult; 10= Very easy): 
Very 
difficult 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
easy 
 
 
 
 
 
 
 
 
 
 
 
 
2.​ Usefulness of the App: Do I find the App a useful tool for tracking your skin disease? 
(0 = No useful; 10= Very useful): 
No 
useful 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
useful 
 
 
 
 
 
 
 
 
 
 
 
 
3.​ Empowerment: Do you consider that the App has allowed you to have greater 
autonomy and control in the follow-up of your disease? 
(0 = Strongly disagree; 10= Strongly agree): 
Strongl
y 
disagre
e 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Strongl
y agree 
 
 
 
 
 
 
 
 
 
 
 
 
4.​ Learning and knowledge: Do you consider that the tool has provided you with 
information to learn more about your disease status? 
(0 = Strongly disagree; 10= Strongly agree): 
Strongl
y 
disagre
e 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Strongl
y agree 
 
 
 
 
 
 
 
 
 
 
 
 
5.​ Satisfaction with the care received. How would you rate the treatment received 
by your doctor through the App? 
(0 = Really bad; 10= Excellent): 
Really 
bad 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Excelle
nt 
 
 
 
 
 
 
 
 
 
 
 
 
6.​ Support: Have you felt more supported during the follow-up of your condition thanks to 
the App? 
(0 = I have felt very unaccompanied; 10= I have felt very accompanied: 
 
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Very 
unacco
mpanie
d 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
accom
panied 
 
 
 
 
 
 
 
 
 
 
 
 
7.​ Overall Satisfaction. Please indicate how satisfied you are with the Legit.Health 
application for remote monitoring of your condition. 
(0 = Very unsatisfied; 10 = Very satisfied): 
Very 
unsatisfied 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Very 
satisfied 
 
 
 
 
 
 
 
 
 
 
 
 
8.​ Grade of recommendation: Would you recommend the use of this app to other 
patients with a skin pathology like yours? 
(0 = I would certainly not recommend it; 10 = I would recommend it): 
Not 
recommend 
it 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
Recommen
d it 
 
 
 
 
 
 
 
 
 
 
 
 
9.​ Other comments:  
 
 
 
 
 
 
 
Thank you for your colaboration 
 
 
 
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ANNEX III. System Usability Scale - SUS 
Please rate from 0 to 5 the following aspects: 
1. I think I would like to use this app frequently 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
2. I found this app unnecessarily complex 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
3. I thought the app was easy to use 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
4. I think I would need help from a technical expert to use the app. 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
5. I found that the various possibilities of the APP were quite well integrated. 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
6. I thought there was too much inconsistency in the app. 
 
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Completely disagree <⸻⸻⸻⸻⸻⸻> Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
7. I think most people would learn to use this app very quickly. 
Completely disagree <⸻⸻⸻⸻⸻⸻> Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
8. I found this app very difficult to use. 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
9. I felt very confident using the app. 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
10. I would need to learn a lot of things before using the app properly. 
Completely disagree  <⸻⸻⸻⸻⸻⸻>  Completely agree 
0 
1 
2 
3 
4 
5 
 
 
 
 
 
 
 
To calculate the SUS score, the contributions of each item must first be summed. The 
contribution of each point will be worth between 0 and 4. For points 1, 3, 5, 7 and 9, the 
contribution will be the position on the scale minus 1. For points 2, 4, 6, 8 and 10, the 
contribution will be 5 minus the position on the scale. The sum of the results is multiplied 
by 2.5 to obtain the overall SUS value. The result will be between 0 and 100. 
 
 
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ANNEX IV. Dermatology Life Quality Index  (DLQI - Dermatology Life Quality 
Index) 
The purpose of this questionnaire is to evaluate to what extent your skin problems have 
influenced your life during the last 7 (seven) days. Please check one box for each question. 
Please check that you have answered ALL questions. Thank you. 
Start time 
What time do you start filling out the 
questionnaire? 
__ __  :  __ __ 
example:  
1 3 : 4 6 
 
Please check one box for each question. 
1. During the last seven days, have you had itching, pain or stinging of your skin? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
 
 
 
 
 
 
2. During the last seven days, have you felt embarrassed or self-conscious because 
of your skin problems? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
3. During the past seven days, have your skin problems interfered with shopping or 
taking care of the house or deck? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
4. During the last seven days, have your skin problems influenced the clothes you 
have worn? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
5. During the past seven days, have your skin problems affected any social or leisure 
activities? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
 
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6. During the last seven days, has it been difficult for you to practice any sport 
because of your skin problems? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
7. During the past seven days, have your skin problems prevented you from working 
or studying? 
☐ Yes 
☐ No  
 
 
 
If "No", during the last seven days, has your skin caused you any problems at 
work or school? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
8. During the last seven days, have your skin problems caused problems with your 
partner or a close friend or family member? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
9. During the past seven days, have your skin problems made your sex life difficult? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
 
 
 
 
10. During the last seven days, has the treatment of your skin been a problem for 
you, e.g., because it has made your home dirty or taken up your time? 
☐ Very much 
☐ Much  
☐ A little 
☐ Not at all  
☐ Not applicable 
 
Questionnaire administration time: 
How long did it take you to answer the questions? 
 
 
Score: 
 
 
Thank you very much for your contribution.  
 
 
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ANNEX V. Data collection notebook 
Attached is an excel file with the variables to be collected        
ANNEX VII. EC Declaration of Conformity 
EC Declaration of Conformity document is attached 
 
 
 
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