Clinical trials: AI (Artificial Intelligence)
Artificial Intelligence (AI)
Effectiveness of Artificial Intelligence Algorithms
Introduction Throughout human history, surgical interventions have been frequently used in human treatment. However, despite their therapeutic properties, the pain experienced by patients, especially in the acute postoperative…
- Trial name
- NCT06770985
- Testing
- Artificial Intelligence
- Where
- Turkey (Türkiye)
- Volunteers
- 601 people
- Sponsor
- Ankara Ataturk Sanatorium Training and Research Hospital
Low Back Pain, Low Back Dysfunction
EFFICACY OF ARTIFICIAL INTELLIGENCE DRIVEN PROGRAM VERSUS TRADITIONAL PHYSICAL THERAPY PROGRAM IN PATIENTS WITH LOW BACK DYSFUNCTION
Low back dysfunction is one of the most common musculoskeletal disorders and is associated with pain, disability, and reduced quality of life.
- Trial name
- AI-LBD (NCT07749833)
- Testing
- AI-Driven Rehabilitation Program, Traditional Physical Therapy Program
- Where
- Egypt
- Volunteers
- 68 people
- Sponsor
- Cairo University
Heart Arrest
Clinical Validation of Vital-PICASO for Predicting Cardiac Arrest Within 24 Hours
The purpose of this retrospective study is to evaluate the clinical performance of Vital-PICASO, an artificial intelligence-based biological signal analysis software designed to predict the risk of in-hospital cardiac arrest…
- Trial name
- NCT07742943
- Where
- South Korea
- Volunteers
- 387 people
- Sponsor
- Huinno AIM
Basal Cell Cancer
AI in Histipathological Diagnosis of Bcc
The goal of this study is to evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm in the histopathological diagnosis of bcc compared to certified dermatopathologists
- Trial name
- AI\bcc (NCT07786376)
- Where
- Egypt
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- Al-Azhar University
Atrial Fibrillation
A Study on the Effectiveness of the Application of an Artificial Intelligence Algorithm for Calibrating PPG With ECG to Improve the Accuracy of Atrial Fibrillation Burden Estimation
Use the ECG watch to collect W-PPG and W-ECG data. Through artificial intelligence algorithms, compare the W-PPG data collected by the ECG watch and the W-PPG data calibrated by the W-ECG data of the ECG watch with the P-ECG data…
- Trial name
- EASE-AF (NCT06552468)
- Testing
- AF monitoring by a smartwatch with PPG
- Where
- China
- Volunteers
- 1,054 people
- Sponsor
- Beijing Anzhen Hospital
AI and GIT
Assessing Knowledge, Attitudes, Trust, Perceived Usefulness, and Barriers to Using Artificial Intelligence (AI) in Gastroenterology Among Clinicians and Patients
-Introduction Innovative technological developments in medical image interpretation, diagnostic support, risk assessment for different illnesses, outcome prognostication, and, in some cases, treatment recommendation have all been…
- Trial name
- NCT07669025
- Testing
- Questionnaire
- Volunteers
- 100 people
- Sponsor
- Sohag University
Gastric Cancer, Prehabilitation
Preoperative Home-based Multimodal Prehabilitation Based on 5G + Artificial Intelligence Mobile Health
The goal of this prospective, multicenter, open-label randomized controlled clinical trial is to evaluate whether a home-based, digitally supervised multi-modal prehabilitation intervention can improve functional capacity…
- Trial name
- NCT07755917
- Testing
- mHealth prehabilitation group, ERAS group
- Volunteers
- 490 people
- Sponsor
- The Affiliated Hospital of Qingdao University
Autism Spectrum Disorder, Child
AI Toothbrush and Visual Pedagogy to Improve Oral Hygiene in Children With Autism Spectrum Disorder
This randomized clinical trial evaluates the effectiveness of an AI-enabled electric toothbrush and visual pedagogy materials in improving oral hygiene among children with autism spectrum disorder (ASD).
- Conditions
- Autism Spectrum Disorder, Child, Oral Health, Artificial Intelligence
- Trial name
- NCT07160517
- Testing
- Visual Pedagogy and Manual Toothbrushing
- Where
- Brazil
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- University of Sao Paulo
Acute Respiratory Failure
Human Algorithm Interactions for Acute Respiratory Failure Diagnosis
Artificial intelligence (AI) shows promising in identifying abnormalities in clinical images. However, systematically biased AI models, where a model makes inaccurate predictions for entire subpopulations, can lead to errors and…
- Trial name
- NCT06098950
- Testing
- Artificial Intelligence model predictions without explanation, Artificial intelligence model predictions with explanation, AI model biased against heart failure
- Where
- United States
- Volunteers
- 457 people
- Sponsor
- University of Michigan
Cardiac Arrest, Cardiopulmonary Resuscitation
Generative AI and Gamified Simulation-Based Train-the-Trainer Basic Life Support Training for High School Teachers in Vietnam
The goal of this randomized controlled trial is to learn whether adding generative artificial intelligence (AI) feedback, gamified practice and a structured Train-the-Trainer component to a one-day simulation-based Basic Life…
- Trial name
- NCT07898891
- Testing
- Generative AI and Gamified Simulation-Based Train-the-Trainer BLS Programme, Conventional Instructor-Led Simulation-Based BLS Training
- Where
- 2 sites in Thailand, Vietnam
- Volunteers
- 56 people, healthy volunteers welcome
- Sponsor
- Eastern International University
Lung Disease
Spirometry Interpretation Performance of Primary Care Clinicians With/Without AI Software
To evaluate whether an artificial intelligence decision support software (ArtiQ.Spiro) improves the diagnostic accuracy of spirometry interpreted by primary care clinicians, as measured by Clinician Diagnostic Accuracy (vs…
- Trial name
- SPIRO-AID (NCT05933694)
- Testing
- Artificial Intelligence-powered Spirometry Interpretation Report
- Where
- United Kingdom
- Volunteers
- 228 people, healthy volunteers welcome
- Sponsor
- Royal Brompton & Harefield NHS Foundation Trust
Emergency Medicine, Diagnostic Errors
Diagnostic Accuracy of Two Large Language Models in Turkish Emergency Department Anamnesis Notes
This retrospective diagnostic accuracy study evaluates two large language models - GPT-4.1 (gpt-4.1-2025-04-14; OpenAI) and Claude Sonnet 4.6 (claude-sonnet-4-6; Anthropic) - as retrospective coding-quality instruments applied to…
- Conditions
- Emergency Medicine, Diagnostic Errors, Artificial Intelligence (AI) in Diagnosis
- Trial name
- LLM-ED-DX-TR (NCT07632859)
- Where
- Turkey (Türkiye)
- Volunteers
- 600 people
- Sponsor
- Marmara University Pendik Training and Research Hospital
Medical Image Integrity Verification
DeepMedFake-Assisted Detection of Synthetic and Discordant Medical Images
This prospective randomized controlled trial will evaluate whether DeepMedFake improves the identification of medical images that require further verification.
- Trial name
- NCT07823023
- Testing
- DeepMedFake
- Where
- China
- Volunteers
- 64 people, healthy volunteers welcome
- Sponsor
- Beijing Friendship Hospital
Stroke, Intracerebral Hemorrhage
AI-assisted Transcranial Duplex Sonography for Early Detection of Intracerebral Haemorrhage: HYPER-AI-SCAN
The goal of this observational study is to evaluate whether transcranial Doppler ultrasound, combined with artificial intelligence (AI), can help identify intracerebral haemorrhage (ICH) in people with acute stroke (both men and…
- Conditions
- Stroke, Intracerebral Hemorrhage, Intracerebral Hemorrhage Basal Ganglia, Intracerebral Haemorrhage
- Trial name
- NCT07319013
- Where
- Spain
- Volunteers
- 500 people
- Sponsor
- Hospital Universitari Vall d'Hebron Research Institute
Cardiovascular Diseases, Valvular Heart Disease
Reliability of Artificial Intelligence (AI)-Augmented Point-of-care Cardiac Ultrasound in the Hands of Internists
The study aim is to test the diagnostic performance of internists interpreting echo images aided by the AISAP CARDIO V0.7 diagnostic support system.
- Trial name
- NCT05455541
- Testing
- AI augmented POCUS examination
- Where
- Israel
- Volunteers
- 300 people
- Sponsor
- Sheba Medical Center
Point-of-care Ultrasound
AI for Gastric POCUS ( Point-of-care Ultrasound)
The goal of this observational study is to train and test an AI (Artificial Intelligence)-based program to assist anesthesiologists in the interpretation of stomach ultrasound images and differentiate a "full" from an "empty"…
- Trial name
- POCUS (NCT07580456)
- Where
- Canada
- Volunteers
- 30 people, healthy volunteers welcome
- Sponsor
- University Health Network, Toronto
Thoracic Diseases, Lung Diseases
AI-Based Assessment of Chest Diseases on Chest X-ray Imaging Using DenseNet-121 and a CheXpert-Trained Model
Chest X-rays are widely used to detect thoracic and lung conditions, but reviewing high volumes of radiographs can lead to workload strain and variation between interpreters.
- Trial name
- NCT07834879
- Volunteers
- 100 people
- Sponsor
- Assiut University
Venous Disease
Training of a Artificial Intelligence Model to Detect Venous Diseases Using PPG Technology
This clinical research aims to evaluate the effectiveness of using Photoplethysmography (PPG) signals combined with Artificial Intelligence (AI) algorithms, for the precise classification and diagnosis of Venous Diseases of the…
- Trial name
- NCT06433024
- Testing
- PPG Diagnostic
- Where
- United Kingdom
- Volunteers
- 20 people, healthy volunteers welcome
- Sponsor
- The Whiteley Clinic
Placenta Accreta Spectrum
Diagnostic Trial of a Vision Transformer-Based Ultrasound AI Model for Placenta Accreta Spectrum
This study develops an end-to-end Vision Transformer (ViT)-based artificial intelligence system for ultrasound-based diagnosis of placenta accreta spectrum (PAS), aiming to improve the accuracy and efficiency of prenatal…
- Trial name
- NCT07643090
- Testing
- Vision Transformer-Based End-to-End Ultrasound Artificial Intelligence Model
- Where
- China
- Volunteers
- 561 people
- Sponsor
- FANG HE
Cerebral Palsy
Pediatric Rehabilitation for Children With Cerebral Palsy Through PVT Using AI to Reduce Spasticity
The study foucs on pediatric rehabilitation for children with cerebral palsy through personalized vibration therapy powered by artificial intelligence.
- Trial name
- NCT06407323
- Testing
- Personalized vibration therapy powered by AI, Physical therapy treatment
- Where
- 2 sites in Pakistan
- Volunteers
- 32 people
- Sponsor
- Superior University