moncefem/clinical-trials-ai-2000-2025 huggingface dataset:
Artificial Intelligence and Hepatocellular Carcinoma
Trial ID: NCT05637788
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2021-07-01
Completion date: 2025-11-01
Sponsor: Humanitas Clinical and Research Center
Collaborators: San Gerardo Hospital; Ospedale "Carlo Poma" - Mantova; Ospedale Centrale di Bolzano; University of Pavia; Morgagni Pierantoni Hospital; Regina Elena Cancer Institute; Universita di Verona; University of Milano Bicocca; Treviso Regional Hospital; Fondazione Policlinico Universitario Agostino Gemelli IRCCS; Miulli General Hospital; Federico II University; Research Institute Against Digestive Cancer IRCAD
Conditions: HCC
Interventions: CT Scan Radiomics Features Extraction
Locations: IRCCS Istituto Clinico Humanitas
Countries: Italy
Enrollment: 535
Age range: 18 Years - None
Sex: ALL

Summary:
To identify new relevant biomarkers for HCC patients and their risk of recurrence. Radiomics data and computer-vision data will be explored for their ability to predict the presence of particular pathological signs of aggressiveness (microvascular invasion and satellitosis), and the prognosis after surgery.

Eligibility criteria:
Inclusion Criteria:

* Age \>= 18 years old.
* Hepatocarcinoma diagnosis confirmed at histological specimen
* Being at the first HCC diagnosis or with a recurrence/persistence disease evaluated and treated for the first time with surgery at the participating center.
* Available contrast-enhanced CT Scan obtained no more than 1 month prior to surgery.

Exclusion Criteria:

* Surgery as a downstaging therapy for transplant
* Patients treated with surgery in case of not-curative intent (palliation, best supportive care, etc).
* Histopathological specimen of combined liver primary neoplasms (e.g. 'epatocolangiocarcinoma').

Outcomes:
Evaluate the association between different radiomics and computer-vision features, and the survival after surgery
Digital Health for Aging: A Multimodal AI-Based Smart Assessment and Rehabilitation Training System for Lumbar Degeneration
Trial ID: NCT07133724
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-08-01
Completion date: 2028-07-31
Sponsor: National Taiwan University Hospital
Conditions: Degenerative Lumbar Spine Diseases
Interventions: AI-Based Smart Assessment and Rehabilitation Training
Locations: National Taiwan University Hospital
Countries: Taiwan
Enrollment: 100
Age range: 50 Years - 80 Years
Sex: ALL

Summary:
This study will integrate wireless wearable sensors, smartphone imaging, and multimodal artificial intelligence (AI) to address the rehabilitation needs of patients with lumbar degeneration. Patients will undergo comprehensive functional assessments, and individualized exercise instruction with real-time feedback will be provided through a smartphone application. The goals of this research are to: (1) develop a multimodal AI-based digital health system combining IMU sensors and smartphone cameras for real-time assessment and interactive rehabilitation training, (2) construct biomechanics- and gait-analysis models to support personalized rehabilitation for patients with lumbar degeneration, and (3) investigate the mechanisms and clinical efficacy of pelvic control exercise training combined with real-time smartphone feedback in improving function and quality of life for aging patients.

Eligibility criteria:
Inclusion Criteria:

1. Age between 50-80 years to capture the typical characteristics of lumbar degeneration in this age group.
2. No history of low back pain lasting more than one week or severe enough to interrupt work within the past year.
3. Normal lumbar functional mobility.
4. Ability to walk independently for more than 10 meters.

Exclusion Criteria:

1. Presence of systemic joint diseases such as ankylosing spondylitis, rheumatoid arthritis, or multiple sclerosis, which may significantly affect lumbar mobility and gait patterns.
2. Central nervous system disorders (e.g., spinal cord injury, stroke, or Parkinson's disease) that may influence gait and motor control.
3. Vestibular system disorders, to avoid balance abnormalities interfering with gait testing.
4. History of spinal or lower limb surgery, as postoperative changes may affect the accuracy of gait data.
5. Inability to communicate or follow instructions.

Outcomes:
Functional assessment: Walking speed; Functional assessment: Walking distance; Functional assessment: 5 Times Sit to Stand Test
Use of Artificial Intelligence in Breast Cancer Screening: Impact of AI-Assisted Single Reading by One Radiologist on Screening Quality Indicators Compared to Standard Double Reading by Two Radiologists Without AI
Trial ID: NCT07075679
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-10-06
Completion date: 2028-10-05
Sponsor: University Hospital Olomouc
Conditions: Breast Cancer Screening; Artificial Intelligence (AI); Breast Cancer Screening and Diagnosis
Interventions: Group with AI iCAD version 3; Group without AI
Locations: University Hospital Olomouc
Countries: Czechia
Enrollment: 8000
Age range: 45 Years - 69 Years
Sex: FEMALE

Summary:
A randomized prospective study comparing the evaluation of mammography images in a breast cancer screening programme by a single radiologist with AI support versus standard double reading by two radiologists without AI support.

Eligibility criteria:
Inclusion Criteria:

* age 45-69, asymptomatic woman participating in breast cancer screening programme

Exclusion Criteria:

* clinical signs of breast disease - indication for diagnostic mammography

Outcomes:
Further assessment rate
An in Silico External Clinical Validation of AI Solutions for Cancer Management in the CHAIMELEON Project. Applied to 4 Target Types of Cancer (Lung, Breast, Prostate and Colorectal), Collected Through the Routine Delivery of Health Care With no Enrolment Conditinos (Real World Data).
Trial ID: NCT06950996
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-09-01
Completion date: 2024-11-01
Sponsor: Instituto de Investigacion Sanitaria La Fe
Collaborators: University of Pisa; University Hospital Rijeka; University of Messina; Istanbul Medipol University Hospital; Centro Hospitalar do Porto; Hospitales Universitarios Virgen del Rocío; IRCCS Policlinico S. Donato; National Cancer Center Affiliate of Vilnius University Hospital Santaros Klinikos; Charite University, Berlin, Germany; Osakidetza; Le Collège des Enseignants de Radiologie de France
Conditions: Breast Cancer; Lung Cancer, Non-Small Cell; Colon Cancer; Rectum Cancer; Prostate Cancer
Interventions: Risk in prostate cancer; Life expectancy in lung cancer; Histological subtype; Staging of colon cancer; invasion in rectum cancer
Locations: Hospital Universitario y Politécnico la Fe
Countries: Spain
Enrollment: 300
Age range: 18 Years - 85 Years
Sex: ALL

Summary:
The goal of this observational study is to see how useful an experimental viewer and AI solutions are for clinicians in their daily work. The investigators want to find out if the AI helps clinicians interpret medical images for different types of cancer.

The AI solutions aim to:

* Classify whether prostate cancer is low or high risk
* Classify the histological subtype in breast cancer
* Estimate the life expectancy of patients with lung cancer
* Determine the size of colon cancer, lymph node involvement and the possibility of metastasis..
* Assess the invasion of sorrounding tissues in the case of rectum cancer. The study will involve clinicians from various centres who will review a set of cases not previously analysed by the AI. Clinicians will do this in two phases: first using only their own expertise and then with the help of the AI solutions.

The technical team want to see if the AI solutions assist clinicians and could become useful in the everyday clinical practice. Clinicians will complete a survey to share their feedback on the usability of the platform and how helpful the AI solutions are.

Eligibility criteria:
Inclusion Criteria:

* patients with an histological confirmation of cancer diagnosis (prostate, lung, breast, colon or rectum)
* availability of radiological images (MR for prostate and rectum, CT for lung and colon or mammographys for breast).
* enough follow up (12 months for prostate, breast and rectum), 18 months for lung, and 24 months for colon.

Exclusion Criteria:

* patients with incomplete or low quality data (radiological, pathological or uncomplete clinical data necessary for the ground truth)

Outcomes:
Usability of experimental viewer with AI tools; Utility of experimental medical images viewer
Changes in Scalp Condition After Using a Moisturizer Containing Celastrol and Cichorium Intybus Root Extract: a Prospective Clinical Trial Using Artificial Intelligence
Trial ID: NCT07459023
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-07-01
Completion date: 2025-12-31
Sponsor: Seoul National University Bundang Hospital
Conditions: Dandruff; Seborrhoeic Dermatitis of the Scalp
Interventions: Ducray Kertyol P.S.O. Concentrate Cream, Ducray Laboratory, France
Locations: Seoul National University Bundang Hospital
Countries: South Korea
Enrollment: 23
Age range: 19 Years - None
Sex: ALL

Summary:
The goal of this clinical trial is to evaluate whether a scalp moisturizer containing celastrol and Cichorium intybus root extract can improve scalp condition in adults aged 19 years or older who require scalp moisturization due to dryness, scaling, erythema, or dandruff. The main questions it aims to answer are:

Does once-daily application of the study moisturizer improve scalp condition from baseline to week 4, as assessed by SPI-AI (Scalp Photographic Index-Artificial Intelligence)?

Does the moisturizer improve scalp biophysical parameters (erythema index, stratum corneum hydration, and transepidermal water loss) and patient-reported symptom severity over the 4-week treatment period?

Participants will:

Apply the study moisturizer once daily at bedtime to dry scalp for 4 weeks and rinse it off the following morning using their usual shampoo.

Attend study visits at baseline (week 0), week 2, and week 4 for scalp imaging, biophysical measurements, symptom questionnaires, adherence assessment, and safety monitoring.

Eligibility criteria:
Inclusion Criteria

* Age ≥19 years
* Presence of scalp erythema, dryness, scaling, or dandruff requiring scalp moisturization

Exclusion Criteria:

* Active infectious scalp dermatoses
* Use of topical or systemic therapies affecting scalp status within 4 weeks prior to enrollment or during the study period
* Inability to comply with the study protocol

Outcomes:
SPI-AI
Pediatric Rehabilitation for Children With Cerebral Palsy Through Personalized Vibration Therapy Powered By Artificial Intelligence: An Innovative Approach to Reduce Spasticity and Improved Motor Function and Quality Of Life
Trial ID: NCT06407323
Status: ACTIVE_NOT_RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2023-10-01
Completion date: 2024-09-01
Sponsor: Superior University
Conditions: Cerebral Palsy
Interventions: Personalized vibration therapy powered by AI; Physical therapy treatment
Locations: Johar pain relief center; Ali Fatima hospital
Countries: Pakistan; Pakistan
Enrollment: 32
Age range: 2 Years - 9 Years
Sex: ALL

Summary:
The study foucs on pediatric rehabilitation for children with cerebral palsy through personalized vibration therapy powered by artificial intelligence.

Eligibility criteria:
Inclusion Criteria:

* Diagnosed spastic CP as per neurologist report, GMFCS level I-III
* Ability to safely withstand intensity of vibrating device.
* have no planned surgery within 5 months before/after entering the study

Exclusion Criteria:

* A bone fracture within 12 weeks of enrollment.
* History of using anabolic agents, glucocorticoids (excluding inhaled), or growth hormone (regardless of dose) for at least 1 month, within the 3 months prior to enrollment.
* History of botulinum toxin injection into the lower limb(s) within the 3 months before enrollment.
* History of an illness or findings on physical examination that might prevent the child from completing the study (e.g., acute thrombosis, tendinitis).

Outcomes:
Modified Ashworth Scale; Quality of life-child Questionnaire
Evaluating Artificial Intelligence-Based Comprehensive Clinical Decision Support for Sepsis and ARDS
Trial ID: NCT07025096
Status: ENROLLING_BY_INVITATION
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-12-05
Completion date: 2026-05
Sponsor: University of Pennsylvania
Collaborators: National Institute of General Medical Sciences (NIGMS)
Conditions: Sepsis; Acute Respiratory Distress Syndrome (ARDS)
Interventions: Artifical Intelligence-Generated Treatment Recommendations
Locations: University of Pennsylvania
Countries: United States
Enrollment: 350
Age range: 18 Years - None
Sex: ALL

Summary:
Sepsis and acute respiratory distress syndrome (ARDS) are common in intensive care units. Managing sepsis and ARDS is inherently complex and requires making numerous decisions under uncertainty. Artificial intelligence (AI) clinical decision support systems (CDSSs) offer a promising approach to support care management for sepsis and ARDS.

The goal of this randomized, survey-based study is to compare treatment recommendations enacted by clinicians to those generated by an AI CDSS. The study will investigate whether an AI CDSS can generate treatment recommendations that are safe, appropriate, and indistinguishable to those provided by real clinicians.

In this study, participants (i.e., critical care clinicians) will review a series of critical care cases (vignettes) in an electronic survey. Each vignette will contain a de-identified case of a patient with sepsis and ARDS as well as treatment recommendations for the case. Participants will assess the safety and appropriateness of each treatment recommendations and answer whether they think the treatment recommendations came from the clinician or an AI CDSS.

Eligibility criteria:
Inclusion Criteria:

* Working as a physician (i.e., MD, DO) or an advanced practice provider (i.e., nurse practitioner, physician assistant)
* Working at a hospital or medical center in medical critical care, anesthesia critical care, surgical critical care, or emergency medicine

Exclusion Criteria:

* Has not completed a residency training program (i.e., medical intern or resident)

Outcomes:
Accuracy of Predicting the Source of Treatment Recommendation
Utilization of Tonal Exercise System to Improve Short- and Long-term Low Back Pain (LBP) Outcomes
Trial ID: NCT04543396
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2020-11-01
Completion date: 2024-06-17
Sponsor: Mayo Clinic
Conditions: Low Back Pain
Interventions: Resistance exercise
Locations: Mayo Clinic in Rochester
Countries: United States
Enrollment: 230
Age range: 18 Years - 65 Years
Sex: ALL

Summary:
This study will assess the effect of incorporating a tonal exercise device into clinical and chiropractic care for lower back pain.

Eligibility criteria:
Subjects seeking treatment for nonspecific LBP will be recruited by their treating therapist, physiatrist, athletic trainer, or chiropractor then enrolled by a clinical research coordinator (CRC). The CRC will assign study IDs and randomize clinical patients into groups based on the each subject's selected treatment of choice. Care will be taken to match subject distribution between groups based on demographics (sex and age), activity level, and subjective pain scores. Lead investigators will remain blinded to group assignments. Subjects will have to complete 2 screening evaluations prior to participation in this study. The first screen will be that the treating physical therapist, physiatrist, athletic trainer, or chiropractor will approve the patient for participation. The second screen will consist of completing two basic activities on the Tonal at minimal weight without being restricted by pain. The two activities will be 10 repetitions on each arm of standing unilateral bicep curl and seated unilateral lateral pulldown. For both activities Tonal resistance will be set at 5 pounds, which is the minimum resistance for the device. This screen will affirm that the subject is capable of completing at least the minimum level of workout provided by the Tonal.

Inclusion Criteria:

* Males and Females between ages 18 and 65
* Seeking physical therapy (PT) or chiropractic care
* Non-specific LBP
* Treatment at Mayo Clinic Rchester

Exclusion Criteria:

* Not able to attend Mayo Clinic Rochester for treatment
* Women who are pregnant

Outcomes:
Patient Pain; PROMIS Subjective Health Assessment score; Kinesiophobia; Isometric Lumbar Strength
Artificial Intelligence to Evaluate Postoperative Pain Based on Facial Expression Recognition and Analgesia Nociception Index
Trial ID: NCT05477303
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2022-06-17
Completion date: 2026-05-09
Sponsor: Seoul National University Bundang Hospital
Conditions: Artificial Intelligence; Facial Expression; Analgesia; Pain, Postoperative
Interventions: taking a picture of a painful facial expression
Locations: Seoul National University Bundang Hospital
Countries: South Korea
Enrollment: 120
Age range: 19 Years - 75 Years
Sex: ALL

Summary:
Patients' subjective complaints about pain intensity are difficult to objectively evaluate, and may lead to inadequate pain management, especially in patients with communication difficulties.

Eligibility criteria:
Inclusion Criteria:

* Patients aged 19-75 years who were scheduled for elective laparoscopic abdominal surgery under general anesthesia
* American Society of Anesthesiology (ASA) class I-II

Exclusion Criteria:

* Patients who have difficulty in communicating and reporting pain
* Underlying diseases: liver, kidney, brain
* Patients with BMI greater than 30 and less than 18.5
* Alcohol or drug dependent patients
* Patients with severe or acute respiratory failure
* Opioid, NSAID allergy
* Patients who are scheduled to be admitted to the intensive care unit after surgery
* Patients who undergo cooperative surgery

Outcomes:
Facial expression; analgesia nociception index; numeric rating scale
Computer Aided Tool for Diagnosis of Neck Masses in Children
Trial ID: NCT05187923
Status: UNKNOWN
Study type: OBSERVATIONAL
Start date: 2021-01-01
Completion date: 2024-12-31
Sponsor: West China Hospital
Conditions: Neck Mass; Thyroglossal Duct Cysts; Branchial Cleft Anomalies; Dermoid and Epidermoid Cysts; Infantile Hemangiomas; Teratomas
Interventions: Artificial Intelligence Algorithm
Locations: West China Hospital, Sichuan University
Countries: China
Enrollment: 1500
Age range: 0 Years - 18 Years
Sex: ALL

Summary:
The aim of this study was to evaluate the diagnostic efficacy of computer aided diagnostic tool for neck masses using machine learning and deep learning techniques on clinical information and radiological images in children.

Eligibility criteria:
Inclusion Criteria:

* Age up to 18 years old
* Receiving no treatment before diagnosis
* With written informed consent

Exclusion Criteria:

* Clinical data missing
* Unavailable radiological images
* Without written informed consent

Outcomes:
The diagnostic accuracy of neck masses with AI-based screening tools in children
Pilot Trial to Evaluate PROblem Solving Therapy and APPLE Watch for College Students (PRO-APPLE)
Trial ID: NCT06333288
Status: COMPLETED
Study type: INTERVENTIONAL
Phase: NA
Start date: 2024-04-15
Completion date: 2024-11-30
Sponsor: University of Illinois at Chicago
Conditions: Alcohol Use Disorder
Interventions: PST-APPLE Watch group; Education-only control group
Locations: University of Illinois at Chicago
Countries: United States
Enrollment: 26
Age range: 18 Years - 25 Years
Sex: ALL

Summary:
The goals of this Pilot Trial are to test the preliminary efficacy of Problom-Solving Therapy (PST)-APPLE Watch in a 2-arm pilot Randomized Control Trial (RCT), vs education only-control to reduce alcohol use disorder symptoms and improve alcohol abstinence.

Eligibility criteria:
Inclusion Criteria:

* Male and female college students aged 18-25 yr
* English-speaking
* Current alcohol use more than or equal to 2 days/week via phone screening
* Completion of AUDIT screening and meet criteria for (past year) mild, moderate or severe AUD during AUDADIS-5 interview
* Completion of written informed consent
* Interested in cutting back alcohol intake or changing his/her drinking
* Baseline screening study visit

Exclusion Criteria:

* Participation in past 6 months in AUD or substance use treatment
* Current use of medications used to treat AUD (e.g., naltrexone)
* Lifetime Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 diagnosis of schizophrenia, bipolar disorder, or any psychotic disorder
* Current use of psychoactive drugs
* Not currently enrolled in college
* Not interested in cutting back alcohol intake or changing his/her drinking
* Pregnancy or intention to become pregnant

Outcomes:
Alcohol abstinence
NutriTrack: An Artificial Intelligence Application for Nutritional and Behavioral Tracking in Patients With Obesity in an Outpatient Obesity Clinic: A Prospective Observational Pilot Study
Trial ID: NCT07588620
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2026-06-15
Completion date: 2026-09-30
Sponsor: Francisco José García González
Collaborators: Hospital San Carlos, Madrid
Conditions: Obesity & Overweight
Interventions: NutriTrack digital health application
Locations: Hospital Clínico San Carlos
Countries: Spain
Enrollment: 50
Age range: 18 Years - None
Sex: ALL

Summary:
NutriTrack is a digital health application designed to support nutritional and behavioral tracking in patients with obesity followed in an outpatient obesity clinic. The application allows patients to record food intake using food photographs, barcode scanning, or manual search, and to register behavioral variables related to eating episodes.

This prospective, single-center, observational pilot study will evaluate the feasibility and usability of NutriTrack in 20 to 50 adult patients with obesity or overweight with comorbidities followed at the Obesity Clinic of Hospital Clínico San Carlos. Participants will use the application for 4 weeks as a complementary tool. The information generated by NutriTrack will be available to healthcare professionals as supportive information and will not replace clinical judgment or modify usual care decisions.

The main outcome is usability measured using the System Usability Scale. Secondary and exploratory outcomes include agreement between artificial intelligence-based nutritional estimates and standard dietitian assessment, adherence to daily food logging, professional perceived clinical utility, changes in eating behavior and emotional regulation scales, and technical feasibility of data export.

Eligibility criteria:
Inclusion Criteria:

* Age 18 years or older.
* Diagnosis of obesity, defined as body mass index 30 kg/m2 or higher, or overweight with comorbidities, defined as body mass index 27 kg/m2 or higher.
* Active follow-up at the Obesity Clinic of Hospital Clínico San Carlos.
* Regular possession and use of a smartphone with iOS or Android operating system.
* Ability to read and understand Spanish.
* Signed informed consent.

Exclusion Criteria:

* Active diagnosed eating disorder, including anorexia nervosa, bulimia nervosa, or binge eating disorder.
* Cognitive impairment preventing autonomous use of the application.
* Simultaneous participation in another nutritional intervention study.
* Inability or refusal to use mobile technology.
* Current pregnancy or breastfeeding.
* Acute medical condition requiring hospitalization during the study period.

Outcomes:
System Usability Scale score