Clinical trials: Deep Learning, active
Atrial Fibrillation, Insulin Resistance
Insulin Resistance as a Predictor of Pulsed Field Ablation Success in Atrial Fibrillation (HOMA-PULSE)
This study investigates whether insulin resistance, a metabolic condition where the body's cells respond poorly to insulin, can predict the success of atrial fibrillation (AF) ablation using pulsed field ablation (PFA)…
- Conditions
- Atrial Fibrillation, Insulin Resistance, Catheter Ablation, Artificial Intelligence
- Trial name
- HOMA-PULSE (NCT07551947)
- Where
- Czechia
- Volunteers
- 120 people
- Sponsor
- Nemocnice AGEL Trinec-Podlesi a.s.
Diabetes (Insulin-requiring, Type 1 or Type 2), Pediatric Diabetes
A Novel Miniature Equine-Assisted Diabetes Education Program for Youth: Evaluating the Diabetes Equine Empowerment Program (DEEP).
The Diabetes \& Equine Empowerment Program (DEEP) is a research study evaluating a novel diabetes education program that combines hands-on interactions with miniature horses and evidence-based diabetes self-management education…
- Conditions
- Diabetes (Insulin-requiring, Type 1 or Type 2), Pediatric Diabetes, Diabetes (DM)
- Trial name
- DEEP (NCT07822555)
- Testing
- Diabetes & Equine Empowerment Program (DEEP)
- Volunteers
- 50 people
- Sponsor
- Nemours Children's Clinic
Type II Endoleak, Abdominal Aortic Aneurysm Enlargement
Deep-learning Predictors of Abdominal Aortic Aneurysm Enlargement in Type II Endoleaks After Endovascular Aortic Repair: The RADAR Study
Background and rationale: Abdominal aortic aneurysm (AAA) is a weakening and enlargement of the main artery in the abdomen. Endovascular aneurysm repair (EVAR) is a minimally invasive treatment used to repair an AAA.
- Trial name
- RADAR (NCT07783126)
- Testing
- Artificial intelligence model analyzing preoperative CT angiography
- Volunteers
- 1,250 people
- Sponsor
- Ente Ospedaliero Cantonale, Bellinzona
Dystonia, Drug Induced Dystonia
Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.
- Conditions
- Dystonia, Drug Induced Dystonia, Parkinson Disease, Essential Tremor
- Trial name
- NCT05317390
- Testing
- DystoniaNet-based diagnosis of isolated dystonia
- Where
- United States
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Massachusetts Eye and Ear Infirmary
Scoliosis Idiopathic Adolescent, Scoliosis
Deep Learning for Early Scoliosis Detection Using mmWave Radar Gait Data
Scoliosis is a sideways curvature of the spine that often develops during childhood and adolescence. When detected early, scoliosis can be managed effectively with non-invasive approaches such as bracing and physiotherapy, while…
- Trial name
- ScoliRadar-AI (NCT07593560)
- Testing
- mmWave Radar Gait Assessment
- Where
- Turkey (Türkiye)
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Gebze Technical University
Subjective Cognitive Decline, Alzheimer Disease
Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns
AHEAD is a prospective, longitudinal, risk-stratified single-arm interventional study enrolling 300 patients with Subjective Cognitive Decline (SCD) at IRCCS San Raffaele Hospital, Milan, Italy.
- Conditions
- Subjective Cognitive Decline, Alzheimer Disease, Mild Cognitive Impairment, Cognitive Decline
- Trial name
- AHEAD (NCT07652931)
- Testing
- High-frequency Transcranial Magnetic Stimulation (TMS), Digital Cognitive Training, Structured Physical Exercise
- Where
- Italy
- Volunteers
- 300 people
- Sponsor
- IRCCS San Raffaele
Aortic Stenosis
Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study
The DETECT-AS Diagnostic Study will assess the performance of artificial intelligence (AI) risk predictions to detect aortic stenosis using results from portable electrocardiogram (ECG) and cardiac ultrasound devices.
- Trial name
- NCT06749145
- Testing
- Portable 1-lead electrocardiogram, Point-of-care ultrasound, AI-ECG risk algorithm
- Where
- 3 sites in United States
- Volunteers
- 410 people, healthy volunteers welcome
- Sponsor
- Yale University
Papillary Thyroid Carcinoma
Multimodal Deep Learning for Lymph Node Metastasis in Thyroid Cancer
Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy in clinical practice, accounting for approximately 85% of all thyroid malignancies.
- Trial name
- NCT07299318
- Testing
- not intervention
- Where
- China
- Volunteers
- 3,200 people
- Sponsor
- West China Hospital
Sepsis
Prediction of Rehospitalization Following a Sepsis Admission Using a Wearable Biopatch
The goal of this observational study is to learn about the utility of biopatches predicting 30-day readmissions in patients discharged from the hospital with sepsis.
- Trial name
- NCT05806762
- Testing
- BioIntellisense
- Where
- United States
- Volunteers
- 200 people
- Sponsor
- University of California, San Diego
Artificial Intelligence, Ultrasonography
Assessment of Liver Diseases Using a Deep-Learning Approach Based on Ultrasound RF-Data
The goal of this clinical trial is to test the performance of neuronal networks trained on ultrasonic raw Data (=radiofrequency data) for the assessment of liver diseases in patients undergoing a clinical ultrasound examination.
- Conditions
- Artificial Intelligence, Ultrasonography, Elasticity Imaging Techniques, Liver Diseases
- Trial name
- LivSPECTRUS (NCT06317181)
- Testing
- Collection of elastography data, Collection of ultrasonic raw data
- Where
- 4 sites in Germany
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Technische Universität Dresden
Gastrectomy for Gastric Cancer, Gastric Cancer
AI-assisted Decision-making of Reoperation for Postoperative Bleeding of Gastric Cancer
The goal of this observational study is to develop and validate a deep learning model to dynamically assess postoperative bleeding risk and assist in decision-making for re-operation in adult patients (≥18 years) diagnosed with…
- Trial name
- NCT07525765
- Where
- China
- Volunteers
- 7,000 people
- Sponsor
- First Affiliated Hospital of Zhejiang University
Pancancer
Retrospective Pathology Foundation Models
By integrating retrospective multimodal data such as pathology and imaging, AI technologies offer novel solutions for disease classification, tumor grading, histological and molecular subtyping, selection of chemotherapy…
- Trial name
- NCT07239297
- Where
- 2 sites in China
- Volunteers
- 2,000 people
- Sponsor
- Nanfang Hospital, Southern Medical University
Cardiac Amyloidosis, Transthyretin Amyloidosis
Retrospective Identification of Scintigraphic Cardiac Amyloidosis (RISCA)
This study aims to determine the positive predictive value of incidental cardiac uptake on bone scintigraphy for diagnosing transthyretin cardiac amyloidosis, in patients who underwent scintigraphy for reasons other than…
- Trial name
- RISCA (NCT06921408)
- Volunteers
- 57 people
- Sponsor
- University Hospital, Lille
Root Canal Treatment, Obturation Quality
Diagnostic Accuracy of a Deep Learning Framework for Automated Evaluation of Root Canal Obturation Quality From Periapical Radiographs
This study aims to develop and evaluate an artificial intelligence (AI)-based system that can automatically assess the quality of root canal fillings using dental X-ray images.
- Trial name
- NCT07684482
- Testing
- Deep learning model
- Volunteers
- 490 people
- Sponsor
- Cairo University
Lung Cancer, Health Screening
Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation.
- Conditions
- Lung Cancer, Health Screening, Early Cancer Detection, Deep Learning
- Trial name
- NCT06910956
- Testing
- CXR-LC
- Where
- United States
- Volunteers
- 1,500 people
- Sponsor
- Massachusetts General Hospital
Glioma
MR Based Survival Prediction of Glioma Patients Using Artificial Intelligence
This registry aims to collect clinical, molecular and radiologic data including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and…
- Trial name
- NCT04215211
- Testing
- Survival prediction for glioma patients
- Where
- China
- Volunteers
- 2,500 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Gastric Cancer, Image
AI Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
This study seeks to develop a deep-learning-based intelligent predictive model for the efficacy of neoadjuvant chemotherapy in gastric cancer patients.
- Conditions
- Gastric Cancer, Image, Pathology
- Trial name
- NCT06035250
- Testing
- Neoadjuvant Chemotherapy
- Where
- 22 sites in China, Italy
- Volunteers
- 200 people
- Sponsor
- Chinese Academy of Sciences
Nasopharyngeal Cancinoma (NPC), Lymph Node Metastasis
A Deep Learning Model for Diagnosing Lymph Node Metastasis in Nasopharyngeal Carcinoma(NPC)
(I) AI Model for Diagnosing Lymph Node Metastasis We developed an AI model to help diagnose whether a single lymph node in nasopharyngeal cancer has spread. The model uses MRI images of the lymph node and the area around it.
- Trial name
- NPC (NCT06829147)
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Sun Yat-sen University
Osteoporosis
Validation of a Deep Learning Tool for Opportunistic Osteoporosis Screening Using Routine Non-Contrast CT Scans
The goal of this clinical trial is to test if an artificial intelligence (AI) tool called DeepBMD can accurately identify people at high risk for osteoporosis using routine chest or abdomen CT scans.
- Trial name
- NCT07739628
- Testing
- DeepBMD model for osteoporosis risk screening
- Where
- China
- Volunteers
- 100 people
- Sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Eye Diseases
Development of a Deep Learning System for Identification of Neuro-Ophthalmological Conditions on Color Fundus Photographs in Emergency Department
In recent years, artificial intelligence (AI) has been widely integrated into the medical field, contributing in particular to improved patient diagnosis.
- Trial name
- DEEP-VISION (NCT06643338)
- Where
- France
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Fondation Ophtalmologique Adolphe de Rothschild