Clinical trials: Deep Learning, open to volunteers
Osteoporosis
AI Model for Bone Mineral Density Prediction From X-Ray Images
Osteoporosis, a pervasive skeletal disorder characterized by diminished bone strength predisposing individuals to an increased risk of fractures, presents a substantial public health challenge globally.
- Trial name
- NCT06652061
- Testing
- Dual Energy X-Ray Absorptiometry Scan (DEXA Scan), X-Ray (Hip and Spine)
- Where
- Bangladesh
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Bangladesh University of Engineering and Technology
Motor Development Assessment, Artificial Intelligence-Based Movement Analysis
AI-Based Video Analysis for Motor Development Assessment in Children
This is a non-interventional, prospective observational study aimed at developing and validating an artificial intelligence-based system for assessing motor development in children using video analysis.
- Trial name
- AMD-AI (NCT07597356)
- Testing
- Observational Assessment Only
- Where
- Turkey (Türkiye)
- Volunteers
- 60 people, healthy volunteers welcome
- Sponsor
- Medipol University
Pediatric Brain Tumors, Glioma
AI-Assisted MRI Molecular Subtyping in Pediatric Brain Tumors
This multicenter observational cohort study aims to develop and validate an artificial intelligence (AI)-assisted diagnostic system for preoperative molecular subtyping of pediatric brain tumors using routine magnetic resonance…
- Conditions
- Pediatric Brain Tumors, Glioma, Medulloblastoma, Ependymoma
- Trial name
- NCT07703605
- Volunteers
- 1,400 people
- Sponsor
- Huashan Hospital
Retained Foreign Object
Prospective Silent Evaluation of AI for Retained Foreign Object Detection
Retained foreign objects, such as surgical sponges, needles, or instruments, are rare but potentially serious complications of surgery.
- Trial name
- RFO-AI (NCT07858162)
- Where
- United States
- Volunteers
- 120 people
- Sponsor
- University of Colorado, Denver
Branch Atheromatous Disease, Acute Ischemic Stroke
Early Identification and Diagnosis of BAD-related Stroke
Branch atheromatous disease (BAD)-related stroke is an important subtype of acute ischemic stroke involving penetrating arteries and is associated with early neurological deterioration.
- Conditions
- Branch Atheromatous Disease, Acute Ischemic Stroke, Cerebral Infarction
- Trial name
- SMART-BAD (NCT07693816)
- Testing
- Multisource clinical-imaging artificial intelligence diagnostic assessment
- Where
- 11 sites in China
- Volunteers
- 1,602 people
- Sponsor
- Peking Union Medical College Hospital
Breast Carcinoma
Research on the Whole-Process Intelligent Diagnosis and Treatment of Digital Breast Tomosynthesis Based on Deep Learning
This study aims to construct a multi-task deep learning model system to mine deep features in DBT images, so as to achieve accurate detection of breast lesions, differential diagnosis of benign and malignant (especially for the…
- Trial name
- NCT07605195
- Testing
- To explore the value of digital breast tomosynthesis based on deep learning in the diagnosis of breast cancer
- Volunteers
- 5,000 people
- Sponsor
- Yunnan Cancer Hospital
Ovarian Cancer, Ovarian Tumor
AI Analysis of CT Scans to Classify Ovarian Tumours as Benign, Borderline or Malignant Before Surgery
The goal of this observational study is to learn if a computer program can tell what type of ovarian tumour a person has from a CT scan taken before surgery. The program uses artificial intelligence (AI).
- Conditions
- Ovarian Cancer, Ovarian Tumor, Borderline Ovarian Tumor
- Trial name
- OvaClass (NCT07883551)
- Where
- 7 sites in Belgium, Netherlands
- Volunteers
- 1,300 people
- Sponsor
- Catharina Ziekenhuis Eindhoven
Gastric (Stomach) Cancer
Development of a Predictive Model for Gastric Cancer Peritoneal Metastasis and Cachexia Using BUB1 and Radiopathomics Data With Deep Learning
This clinical trial aims to develop a predictive model for gastric cancer (GC) peritoneal metastasis and cachexia by integrating BUB1 gene data with radiological and pathological data using advanced deep learning techniques.
- Trial name
- BUDDLE (NCT06858644)
- Testing
- BUB1-Integrated Deep Learning Model for Gastric Cancer Metastasis and Cachexia Prediction
- Volunteers
- 500 people
- Sponsor
- Qun Zhao
New Onset Diabetes After Transplantation
Post-Transplant Diabetes Outcomes Prediction
Chronic Kidney disease (CKD) is a major global health burden and represents one of the most common non-communicable diseases. In Europe, CKD affects over 50 million people, representing approximately 10% of the adult population.
- Trial name
- PERCEIVE (NCT07512804)
- Testing
- Whole genome sequencing (WGS)
- Where
- Italy
- Volunteers
- 120 people
- Sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Epilepsy Intractable
Neuronal Mechanisms of Learning and Utilizing Abstract Representations
The purpose of this study is to examine how memories of past experiences are used to guide behavior in novel situations through the cognitive process of abstraction.
- Trial name
- NCT07454785
- Testing
- Cedrus RB-844 response pad; Adtech Behnke-Fried micro-electrodes; Neurolynx electrophysiology system; Blackrock Cerestim stimulator
- Where
- United States
- Volunteers
- 114 people
- Sponsor
- Cedars-Sinai Medical Center
Cholecystectomy, Surgical Video Identification
Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning
Laparoscopic cholecystectomy is a common surgical procedure, but it carries the potential for bile duct injury and other surgical risks.
- Trial name
- NCT07158372
- Testing
- AI-assisted Intraoperative Anatomy Analysis
- Where
- 5 sites in China
- Volunteers
- 200 people
- Sponsor
- Chinese Academy of Sciences
Ventricular Dysfunction, Left, Ventricular Function, Left
Federated Learning for Point-of-Care Cardiac Ultrasound
This prospective, multicenter study will evaluate a federated machine-learning system designed to analyze focused cardiac point-of-care ultrasound examinations.
- Conditions
- Ventricular Dysfunction, Left, Ventricular Function, Left, Echocardiography, Ultrasonography
- Trial name
- FL-POCUS (NCT07800962)
- Testing
- Focused Cardiac Point-of-Care Ultrasonography, FL-POCUS Federated Machine-Learning Analysis System
- Where
- United States
- Volunteers
- 3,000 people
- Sponsor
- Truway Health, Inc.
Ovarian Cancer
Ovarian Cancer Identification on CT Using Deep Learning
Ovarian cancer remains the deadliest gynecologic malignancy, with poor survival rates largely due to late-stage diagnosis. Early detection is crucial, yet no universally accepted screening method exists.
- Trial name
- NCT06851429
- Where
- 2 sites in Taiwan
- Volunteers
- 12,578 people, healthy volunteers welcome
- Sponsor
- Chang Gung Memorial Hospital
Pancancer
Prospective Pathology Foundation Models
Histopathology remains the gold standard for disease diagnosis, yet faces challenges including pathologist shortages and diagnostic model limitations.
- Trial name
- NCT07157618
- Where
- 2 sites in China
- Volunteers
- 2,000 people
- Sponsor
- Nanfang Hospital, Southern Medical University
Healthy Subjects or Volunteers
Training and Testing Database for IMU Based Gait Analysis Methods
The goal of this study is to establish a high-quality, synchronised dataset of gait events (GE) by simultaneously collecting inertial measurement unit (IMU) data and validated ground truth detections using a Vicon motion capture…
- Trial name
- IMU-GAIT (NCT07236008)
- Where
- Belgium
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Vrije Universiteit Brussel
Non-Alcoholic Fatty Liver Disease
Feasibility Study of Deep Learning-based MDixon Quant for Quantitative Assessment of Chemotherapy-induced Fatty Liver
The purpose of this study is to quantitatively assess the changes in liver fat content in cancer patients before and after treatment.
- Trial name
- NCT06735118
- Testing
- Neoadjuvant chemotherapy
- Where
- China
- Volunteers
- 120 people, healthy volunteers welcome
- Sponsor
- Yunnan Cancer Hospital
Major Adverse Cardiovascular and Cerebrovascular Events (MACCE)
Prospective Validation of DL Model for Postoperative MACCE Prediction
This study aims to prospectively validate a deep learning model developed using retrospective data to predict major adverse cardiac and cerebrovascular events (MACCE) occurring within 30 days after non-cardiac surgery.
- Trial name
- NCT07054502
- Where
- South Korea
- Volunteers
- 7,000 people
- Sponsor
- Seoul National University Hospital
Systemic Sclerosis
Chest CT Biomarkers as Prognostic Predictors in SSc-ILD
The goal of this retrospective observational study is to investigate whether novel imaging biomarkers of airways, vessels, and overall extent of fibrosis at baseline predict ILD progression, vasculopathy development, and survival…
- Trial name
- NCT06472362
- Testing
- HRCT biomarkers
- Where
- 7 sites in France, Germany and 2 more
- Volunteers
- 1,000 people
- Sponsor
- Royal Brompton & Harefield NHS Foundation Trust
Pulmonary Fibrosis, Interstitial Lung Disease
Retrospective Validation of AccuPulmo CT Portal for Detecting Pulmonary Fibrosis on Chest CT
This retrospective observational study evaluates the diagnostic performance of AccuPulmo CT Portal, an artificial intelligence-assisted medical imaging software, for detecting pulmonary fibrosis on pre-existing chest computed…
- Trial name
- ACCUPULMO-FIBR (NCT07761377)
- Testing
- AccuPulmo CT Portal
- Where
- Taiwan
- Volunteers
- 900 people
- Sponsor
- Taichung Veterans General Hospital
Hypertension, Pulmonary, Heart Failure With Reduced Ejection Fraction
Deep Learning Detection of Pulmonary Hypertension and Low Ejection Fraction Via Digital Stethoscope and 3-Lead ECG
This is a prospective, observational study evaluating whether heart sounds (phonocardiograms) and three-lead electrocardiograms (ECGs) recorded using the Eko CORE 500 digital stethoscope can help detect pulmonary hypertension…
- Trial name
- PH ELEFT 2-0 (NCT07087613)
- Testing
- Eko CORE 500 Digital Stethoscope
- Where
- 4 sites in United States
- Volunteers
- 3,850 people
- Sponsor
- Eko Devices, Inc.