moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Impact of an Artificial Intelligence Platform (DERM) on the Healthcare Resource Utilisation (HRU) Needed to Diagnose Skin Cancer When Used as Part of a United Kingdom-based Teledermatology Service
Trial ID: NCT04123678
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2020-02-26
Completion date: 2021-08-06
Sponsor: Skin Analytics Limited
Collaborators: Innovate UK
Conditions: Melanoma; Non-melanoma Skin Cancer
Interventions: Deep Ensemble for the Recognition of Malignancy (DERM)
Locations: Chelsea and Westminster Hospital
Countries: United Kingdom
Enrollment: 700
Age range: 18 Years - None
Sex: ALL

Summary:
This study aims to provide an initial assessment of the potential impact DERM could have on the number of onward referrals for a face to face dermatologist review and/or biopsy from a teledermatology-based service, and to improve the understanding of the patient pathways that exist.

Eligibility criteria:
Inclusion Criteria:

* Participant is willing and able to give informed consent for participation in the study,
* Male or Female, aged 18 years or above,
* Has at least one suspicious skin lesion which is being photographed as part of Standard of Care (SoC),
* In the Investigators opinion, able and willing to comply with all study requirements.

Exclusion Criteria:

* Any other significant disease or disorder which, in the opinion of the Investigator, may either put the participants at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.

Outcomes:
Referral rate
Artificial Intelligence (AI) Empowered Smile Simulations: Do They Accurately Predict Actual Post Treatment Outcomes
Trial ID: NCT06123585
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2018-01-01
Completion date: 2020-07-05
Sponsor: Nourhan M.Aly
Conditions: Malocclusion
Interventions: Invisalign® SmileView™; Invisalign aligners
Locations: Private orthodontic offices of Invisalign Diamond Plus Elite
Countries: United Arab Emirates
Enrollment: 24
Age range: 18 Years - None
Sex: ALL

Summary:
The aim of the present study is to assess the predictability of Invisalign® SmileView™ for digital AI smile simulation in comparison to actual smile treatment outcomes, using various smile assessment parameters.

Eligibility criteria:
Inclusion Criteria:

* healthy systemic condition with no chronic diseases
* no previous orthodontic treatment
* adequate oral hygiene
* a healthy periodontium.

Exclusion Criteria:

* chronic diseases
* previous orthodontic treatment
* poor oral hygiene
* periodontal diseases

Outcomes:
Smile line; Smile arc; The most posterior teeth displayed; The philtrum height; Commissure height; Smile width/Inter-commissure width; Smile index; Maxillary inter-canine width; Buccal corridor; Amount of lower incisor show
In Vivo Computer-aided Prediction of Polyp Histology on White Light Colonoscopy
Trial ID: NCT03775811
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2019-01-01
Completion date: 2022-12-31
Sponsor: Hospital Clinic of Barcelona
Collaborators: Instituto de Salud Carlos III
Conditions: Colonoscopy; Histology; Computer-aided Diagnosis; Artificial Intelligence; Colorectal Polyp; Adenoma Colon Polyp; Hyperplastic Polyp
Interventions: AUTOMATED POLYP CLASSIFICATION
Locations: Hospital Clínic de Barcelona
Countries: Spain
Enrollment: 90
Age range: 18 Years - None
Sex: ALL

Summary:
Our group, prior to the present study, developed a handcrafted predictive model based on the extraction of surface patterns (textons) with a diagnostic accuracy of over 90%24. This method was validated in a small dataset containing only high-quality images.

Artificial intelligence is expected to improve the accuracy of colorectal polyp optical diagnosis. We propose a hybrid approach combining a Deep learning (DL) system with polyp features indicated by clinicians (HybridAI). A pilot in vivo experiment will carried out.

Eligibility criteria:
Inclusion Criteria:

* Age \> 18 years
* Approval of participation in the study. Signature of informed consent
* Patients with at least one polyp of any size/morphology diagnosed in a routine or screening colonoscopy
* Endoscopies performed with high definition endoscopes

Exclusion Criteria:

* Age \<18 years
* Refusal to participate in the study
* Polyps partially resected in a previous endoscopy
* Patients with inflammatory disease
* Impossibility to wash remains of stool or mucus on the surface of the polyp

Outcomes:
Accuracy of the computer-aided system for predicting polyps histology in real clinical practice
Long-Term Evaluation of TAILORED Vs Anatomical Ablation Strategy for Persistent Atrial Fibrillation
Trial ID: NCT06825104
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-03-06
Completion date: 2027-12-31
Sponsor: Volta Medical
Conditions: Atrial Fibrillation
Interventions: Volta AF-Xplorer; Dispersion ablation + PVI; PVI
Locations: CHU Lyon, Hôpital Louis Pradel; Pôle Santé République; Hôpital Saint Philibert; Hôpital Saint-Joseph Marseille; Hôpital Privé Jacques Cartier; Hôpital Privé du Confluent; Polyclinique Saint George; Centre Cardiologique du Nord; Clinique Rhéna; Clinique Pasteur; CHRU Nancy, Institut Lorrain du coeur et des vaisseaux; Klinikum Coburg; German Heart Center
Countries: France; France; France; France; France; France; France; France; France; France; France; Germany; Germany
Enrollment: 278
Age range: 18 Years - None
Sex: ALL

Summary:
The TAILORED-LT study is conducted as an extension follow-up until 5 years of the initial TAILORED-AF study (NCT04702451), in order to demonstrate the long-term superiority in terms of freedom of atrial fibrillation (AF) of a tailored ablation strategy targeting areas of spatio-temporal dispersed electrograms in combination with pulmonary veins isolation (PVI) over an anatomical ablation strategy targeting PVI alone for the initial ablation procedure of persistent AF.

Eligibility criteria:
Inclusion Criteria:

* Patient who participated in the Tailored AF study
* Patient not withdrawn during the 12-month follow-up period post-index procedure in the Tailored AF study
* Patient able and willing to provide written informed consent to participate in this extension Tailored-LT study

Exclusion Criteria:

* Person deprived of liberty or under guardianship
* Person unable to undergo a medical monitoring for geographical, social or psychological reasons

Outcomes:
Long-term freedom from documented atrial fibrillation (AF) after one ablation procedure
CaRi-Heart® Assessment of Risk and Evaluation of Inflammation in Coronary CT Angiography (CARE-CCTA): A Prospective U.S. Community-Based Study on the Impact of CaRi-Heart® Analysis in Patients Undergoing CCTA for Coronary Artery Disease
Trial ID: NCT07220304
Status: NOT_YET_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-12
Completion date: 2028-07
Sponsor: Corazon Medical PC
Conditions: Coronary Artery Disease; Atherosclerosis; Cardiovascular Inflammation
Interventions: CaRi-Heart® Analysis
Locations: Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging; Corazon Imaging
Countries: United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States; United States
Enrollment: 15000
Age range: None - None
Sex: ALL

Summary:
This study evaluates the use of CaRi-Heart® analysis, an artificial-intelligence (AI) software tool that measures inflammation in the coronary arteries using images already captured during a standard Coronary CT Angiography (CCTA) exam. The goal is to determine whether the additional information provided by CaRi-Heart® changes clinical decision-making and helps improve early identification and management of coronary artery disease in community imaging centers. Patients who undergo CCTA as part of their regular care will be invited to have their scans analyzed using CaRi-Heart® at no extra cost, time, or radiation.

Eligibility criteria:
Inclusion Criteria:

1. Clinically indicated CCTA undertaken for evaluation of coronary artery disease.
2. Ability to provide written informed consent
3. Patient between 18 and 80 years old

Exclusion Criteria:

\- 1. History of surgical revascularization (coronary artery bypass graft, CABG) 2. CCTA undertaken for structural heart disease evaluation (e.g. transcatheter aortic valve replacement (TAVR) 3. The CCTA is of poor quality or partly unanalysable due to artifacts, such as motion-artifacts, breathing-artifacts, stack-artifacts or blooming-artifacts.

4\. Inability to provide required health information 5. Pregnancy or any known contraindication for CCTA

Outcomes:
Change in clinical management decisions following CaRi-Heart® analysis
Utilization of Artificial Intelligence for the Development of an EUS-convolution Neural Network Model Trained to Differentiate Pancreatic Cancer From Other Pancreatic Solid Lesions
Trial ID: NCT05476978
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2022-07-01
Completion date: 2024-01-24
Sponsor: Huazhong University of Science and Technology
Collaborators: The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School; LanZhou University
Conditions: Pancreatic Ductal Adenocarcinoma; Pancreatitis, Chronic; Pancreatic Neuroendocrine Tumor; Autoimmune Pancreatitis
Interventions: EUS-AI model
Locations: Tongji hospital, Tongji Medical College, Huazhong University of Science and Technology
Countries: China
Enrollment: 130
Age range: 18 Years - None
Sex: ALL

Summary:
We aim to develop an EUS-AI model which can facilitate clinical diagnosis by analyzing EUS pictures and clinical parameters of patients.

Eligibility criteria:
Inclusion Criteria:

* Patients who underwent EUS using a curved line array echoendoscope (GF-UCT260; Olympus Medical Systems) since 2014 in our affiliation.
* For each patient, all available native EUS pictures are included.
* Patients' diagnosis are validated by surgical outcomes or fine-needle aspiration (FNA) findings and have a compatible clinical course with a follow-up period of more than 6 months.

Exclusion Criteria:

* The image is of poor quality.
* The images contain unique marks which can potentially bias the model, such as the biopsy needle.

Outcomes:
The model's ability to differentiate pancreatic cancer from other pancreatic solid lesion
Supporting Health Care Professionals in Hospital and Primary Care to Promote Adequate HIV Risk and Indicator Condition Driven Testing in Routine Care.
Trial ID: NCT05225493
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2020-01-01
Completion date: 2024-05
Sponsor: Erasmus Medical Center
Collaborators: Huisartspraktijk Gezondheidscentrum Mathenesserlaan; TU Delft department of Artificial Intelligence and MyTomorrows; Huisartsen Groep Rotterdam; AwareHIV Project Group; Huisartspraktijk Handellaan; Huisartspraktijk Leerdam; Huisartspraktijk Capelle ad IJssel; Leiden University Medical Center; Maasstadziekenhuis; Rijnstate Hospital; Medical Center Haaglanden
Conditions: HIV Infections; Primary Health Care; Acquired Immunodeficiency Syndrome; Sexually Transmitted Diseases, Viral; Herpes Zoster; Dermatitis, Seborrheic; Pneumonia; Infectious Mononucleosis; Psoriasis; Candida Infection; Lymphadenopathy; Uterine Cervical Dysplasia; Weight Loss; Diarrhea Chronic; Leukopenia; Thrombocytopenia; AIDS Defining Illness; HIV Indicator Condition
Interventions: Peer to peer feedback; HIV rapid test
Locations: Carlijn CCE Jordans
Countries: Netherlands
Enrollment: 1500
Age range: 18 Years - None
Sex: ALL

Summary:
Patients are frequently evaluated by physicians for medical work-up of HIV indicator conditions in hospital and in primary care at the general practitioner. Testing for HIV is indicated with HIV indicator disorder but often omitted in clinical work-up. Besides the fact that HIV testing is forgotten, there are other reasons such as an underestimation of the risk of HIV in the event of indicator disorders, stigma and difficulties in discussing the test with a patient. Also and more relevant for primary care than for the hospital, practical challenges can exist for a patient to go to a laboratory, or costs are a hurdle.

This project focuses on improving HIV indicator condition driven testing in different settings of the HIV epidemic, initially in the Netherlands as low HIV prevalence setting followed by an assessment of its benefit in different international settings. A specific focus will also be on the Rotterdam area in the Netherlands which has a high prevalence of undiagnosed HIV in the Netherlands. The ultimate aim is to decrease the number of undiagnosed HIV in populations, improve the 90-90-90 HIV cascade of care goals particularly its first pillar, and to help supporting the UNAIDS goal to end HIV/AIDS

Eligibility criteria:
Inclusion Criteria:

* Diagnosis of an HIV indicator conditions.

Exclusion Criteria:

* Below 18 years of age
* Recent HIV test (\< 12 months, except for mononucleosis-like disease and STDs)

Outcomes:
The number of adequately performed HIV tests of identified HIV indicator conditions in relation to the total number of identified HIV indicator conditions by physicians in hospital settings during the project.; The number of adequately performed HIV tests of identified HIV indicator conditions in relation to the total number of identified HIV indicator conditions by general practitioners in primary care during the project.
NUTRITIONAL INTERVENTION STUDY to EVALUATE the EFFECT of ACHETA DOMESTICUS POWDER CONSUMPTION on GLUCOSE HOMEOSTASIS and INTESTINAL DYSBIOSIS in HEALTHY and PREDIABETIC POPULATION
Trial ID: NCT06622616
Status: NOT_YET_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-01
Completion date: 2027-11
Sponsor: María Isabel Espinosa
Collaborators: Biomedical Research Institute Sols-Morreale (CSIC-UAM); Centro de BiologÃ-a Molecular Severo Ochoa, Spain (CBMSO); Epidisease S.L; NUTRINSECT
Conditions: Insulin Resistance; Type 2 Diabetes Mellitus with Features of Insulin Resistance
Interventions: EVALUATE THE EFFECT OF ACHETA DOMESTICUS POWDER CONSUMPTION ON GLUCOSE HOMEOSTASIS AND INTESTINAL DYSBIOSIS
Enrollment: 120
Age range: 18 Years - 65 Years
Sex: ALL

Summary:
A nutritional intervention study is proposed to evaluate the association between the consumption of A. domesticus (insect protein) powder and the effect on insulin resistance and the microbiome, in order to generate personalized nutrition strategies through its analysis with artificial intelligence.

This study is expected to involve 120 healthy volunteers between 18 and 65 years old, with or without insulin resistance, who will be recruited by IMDEA-Food. This is a 12-week nutritional intervention study, so you must come to Institute IMDEA-Food for a first screening visit (V0) and, if you meet the study inclusion criteria and are still interested in volunteering for the study, you will be informed about the study, sign the informed consent form and be scheduled for 2 more visits (V1 or initial zero-time, and V2 or final) at IMDEA-Food\&#39;s facilities.

Eligibility criteria:
Inclusion Criteria:

* Men and women between 18 and 65 years of age.
* Adequate cultural level and understanding of the clinical study.
* Agree to participate voluntarily in the study and give their informed consent in writing.

Exclusion Criteria:

* Subjects with dementia, mental illness or decreased cognitive function that prevents understanding of the study.
* Subjects with celiac disease or serious diseases (tumour, immunological, intestinal, metabolic, cardiovascular processes, etc.).
* BMI \&lt; 18 or ≥ 35.
* Pregnant or breastfeeding women.
* Being a socially vulnerable person.
* Subjects whit chronic pharmacological treatment for weight loss, insulin or antibiotic treatment in the month prior to the start of the intervention or during it.
* Subjects with food allergies, especially to mollusks and their by-products, dust mites, chickpeas or soy (the product may contain traces of soy and gluten).

  * Subjects who refuse to be monitored by sensors, collect samples, draw blood and nutritional visits.
  * Subjects who reject the consumption of products made with alternative proteins (insect powder).

Outcomes:
insulin resistance (HOMA)
Dental Hygienists and Dentists as Providers of Oral Mucosa Screening and Brush Biopsies of Mucosal Lesions and Automated Artificial Intelligence Analysis of Cytology
Trial ID: NCT04081038
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2019-08-31
Completion date: 2023-06-15
Sponsor: Dalarna County Council, Sweden
Conditions: Oral Cancer
Interventions: Brush biopsy
Locations: Kristina Edman; Public Dental Service
Countries: Sweden; Sweden
Enrollment: 100
Age range: 18 Years - None
Sex: ALL

Summary:
In 2007, The World Health Assembly (WHA) adopted a resolution to prevent oral cancer. The resolution urged the member states to ensure that measures against oral cancer was integrated into a national cancer control program by engaging and train dental personnel in screening, early diagnosis and treatment. Oral cancer is a severe oral health issue as it is potentially fatal and is the 5-6 most common tumor with approximately 275,000 cases for oral and 130,300 cases for pharyngeal cancers, excluding nasopharynx, globally. In Sweden,1000 new cases yearly is discovered and it is increasing. The explanation is an aging population and an increase in tonsil and tongue cancers caused by HPV, especially in younger subjects. This is due to changing sexual habits. Tumors caused by tobacco and alcohol are constant. Despite the decreasing prevalence of smoking and certain smoking-associated cancers, an increased incidence of tonsillar cancer has been seen in both Finland and Sweden. High risk HPV (hrHPV) oral cancer is also increasing.

Eligibility criteria:
Inclusion Criteria:

* Patients over 18 years of age
* Understand Swedish

Exclusion Criteria:

* Under 18 years of age
* Not understanding the Swedish language
* Previously mouth cancer diagnose

Outcomes:
Brush biopsy
Development and Validation of a System Based on Digital Face Recognitation for Pain Assessment in Children's Emergency
Trial ID: NCT05527600
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2023-03-07
Completion date: 2023-09-12
Sponsor: Centre Hospitalier Universitaire de Nice
Conditions: C23.888.592.612.081
Interventions: intensity of acute pain evaluation
Locations: CHU de Nice; Hopital pédiatrique Fondation Lenval
Countries: France; France
Enrollment: 2500
Age range: 0 Days - 18 Years
Sex: ALL

Summary:
Accurate assessment of pain in Pediatric Department is challenging. However, recent publications highlight that children do not receive optimal pain management, particularly in Emergency Departments.

An Artificial Intelligence-based tool could help physicians to optimize analgesia use.

Eligibility criteria:
Inclusion Criteria:

* Child under 18
* Informed and written consent of a parent or guardian (only 1 accompanying person allowed).

Exclusion Criteria:

* Language barrier.
* Refusal to participate by parents/children
* Sign of collapsus, or in serious clinical condition (stage I or II) requiring absolute emergency care,
* Delayed mental or staturo-ponderal development
* Facial injury or wound, presence of a bandage on the face, pre-existing facial deformity

Outcomes:
assessment of The intensity of acute pain with the EVENDOL Scale; assessment of The intensity of acute pain with the VAS Scale; the facial expression captured by short video
Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development: a Randomized Control Trial
Trial ID: NCT06847932
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-07-01
Completion date: 2026-10-01
Sponsor: National Defense Medical Center, Taiwan
Conditions: Atrial Fibrillation (AF); Premature Atrial Complexes; Atrial Arrhythmias; Artificial Intelligence (AI); Electrocardiogram
Interventions: AF-predict AI-ECG alert system guided management
Locations: Tri-Service General Hospital
Countries: Taiwan
Enrollment: 14726
Age range: 40 Days - 85 Days
Sex: ALL

Summary:
Our study aimed to use an AF-predict AI-ECG alert system to help physicians identify patients who need to wear a continuous cardiac rhythm monitor for new diagnoses of atrial fibrillation (AF), atrial flutter (AFL), or atrial arrhythmia with high AF risk, including premature atrial complexes (PAC) ≥ 500/24hr, burst PACs \> 20 beats, non-sustained AF/AFL.

Eligibility criteria:
Inclusion Criteria:

* Patients in the inpatient department or the outpatient department
* Patients need to have at least one electrocardiogram within one year

Exclusion Criteria:

* Diagnosis of atrial fibrillation/atrial flutter
* History of atrial fibrillation/atrial flutter catheter ablation
* Patients with cardiac implantable electronic devices
* Any documented electrocardiogram showed atrial fibrillation/atrial flutter and pacing rhythm
* History of received rhythm control medications for atrial arrhythmia, including Class I and Class III antiarrhythmic drugs
* Any reasons indicate for anti-coagulant agents, including vitamin K antagonist and non-vitamin K antagonist oral anticoagulant

Outcomes:
Latent atrial fibrillation
xrAI - Improving Quality and Efficiency in Chest Radiograph Interpretation by Radiologists
Trial ID: NCT04221100
Status: WITHDRAWN
Study type: INTERVENTIONAL
Phase: NA
Start date: 2021-03
Completion date: 2021-05
Sponsor: 1QB Information Technologies Inc.
Conditions: Pulmonary Disease
Interventions: Radiograph interpretation for pulmonary abnormalities
Enrollment: 0
Age range: None - None
Sex: ALL

Summary:
xrAI (pronounced "X-ray") serves as a clinical assistance tool for trained clinical professionals who are interpreting chest radiographs. The tool is designed as a quality control and adjunct, limited, clinical decision support tool, and does not replace the role of clinical professionals. It highlights areas on chest radiographs for review by an interpreting clinician.

The objective of this study is to utilize machine learning and artificial intelligence algorithms (xrAI) to improve the quality and efficiency in the interpretation of chest radiographs by radiologists.

The hypothesis is that the addition of xrAI's analysis will reduce inter-observer variability in the interpretation of chest radiographs and increase participants' sensitivity, recall, and accuracy in pulmonary abnormality screening.

Eligibility criteria:
Inclusion Criteria:

* Radiologist currently practicing at a Pureform Radiology clinic in Calgary, Canada.

Exclusion Criteria:

* Radiologists not currently practicing at a Pureform Radiology clinic in Calgary, Canada.
* Physicians currently practicing at a Pureform Radiology clinic in Calgary, Canada, but that are not radiologists by training.

Outcomes:
Number of abnormalities identified divided by number of total of images analyzed (accuracy); Number of true abnormalities identified divided by the total of abnormalities identified (precision); Number of true abnormalities identified divided by the sum of true abnormalities identified and abnormalities missed (recall)