Clinical trials: Deep Learning, open to volunteers
Carotid Stenosis
Risk Prediction Model for Cerebrovascular Events in Carotid Artery Stenosis
Atherosclerotic carotid artery stenosis is a major cause of stroke, and early identification of high-risk patients combined with surgical intervention can significantly reduce stroke risk.
- Trial name
- NCT06452173
- Testing
- Plasma, carotid high-resolution magnetic resonance imaging
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Beijing Tiantan Hospital
Paediatric Patients
A Fast, Quiet, Artificial Intelligence-based PET/MR Solution for Paediatric Diseases
To investigate the feasibility of deep learning-assisted rapid silent PET/MR in pediatric applications.
- Trial name
- NCT06709690
- Where
- China
- Volunteers
- 35 people
- Sponsor
- Ruijin Hospital
Neoplasms (Cancer / Tumors), Colorectal Neoplasms
A Preregistered Multi-Cohort Evaluation of the FATHOM AI System for Molecular Testing Prioritization to Support Clinical Trial Enrollment
Many clinical trials evaluating cancer treatments require patients to undergo testing for specific molecular markers as part of eligibility screening, typically using immunohistochemistry or sequencing.
- Conditions
- Neoplasms (Cancer / Tumors), Colorectal Neoplasms, Lung Neoplasms, Endometrial Neoplasms
- Trial name
- FATHOM (NCT07814872)
- Where
- United States
- Volunteers
- 30,000 people
- Sponsor
- Harvard Medical School (HMS and HSDM)
Endodontic Retreatment, Non-surgical Retreatment
Development and Validation of a Deep Learning Model to Predict Endodontic Retreatment Difficulty From Periapical Radiographs
The aim of this study is to develop and evaluate an artificial intelligence-based model capable of analyzing periapical radiographs of maxillary and mandibular molars to predict the difficulty level of non-surgical root canal…
- Conditions
- Endodontic Retreatment, Non-surgical Retreatment, Endodontics, AI (Artificial Intelligence)
- Trial name
- Ai Retreatment (NCT07611279)
- Testing
- Deep Learning Model to Predict Endodontic Retreatment Difficulty from Periapical Radiographs
- Volunteers
- 123 people
- Sponsor
- Cairo University
Nasopharyngeal Cancinoma (NPC), Distant Metastasis
Development and Validation of a Deep Learning Model to Predict Distant Metastases in Nasopharyngeal Carcinoma Using Whole Slide Imaging and MRI
An AI model was developed to predict the likelihood of distant metastasis in patients with nasopharyngeal cancer based on pathology slides and MRI scans of the primary tumor.
- Trial name
- NCT06831357
- Where
- 2 sites in China
- Volunteers
- 500 people
- Sponsor
- Sun Yat-sen University
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
Parkinson Disease, Alzheimer Disease
Application of AI Technology for the Diagnosis and Treatment of Geriatric Diseases
1) Characteristics of handwriting, gait, speech, eye movements, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers in patients with Alzheimer's disease.
- Conditions
- Parkinson Disease, Alzheimer Disease, Nervous System Diseases, Geriatric Diseases
- Trial name
- NCT06295263
- Testing
- Handwriting, gait, speech, eye movements, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers
- Where
- China
- Volunteers
- 460 people, healthy volunteers welcome
- Sponsor
- Qilu Hospital of Shandong University
Root Canal
AI-Based Root Canal Length, Curvature, and Morphology Assessment Using CBCT
The primary aim of this study is to develop, evaluate, and validate a deep learning-based software system capable of generating automated, comprehensive clinical reports that detect, segment, and quantify root canal curvature…
- Trial name
- NCT07843992
- Testing
- AI-Based Deep Learning System for Root Canal Assessment
- Volunteers
- 155 people, healthy volunteers welcome
- Sponsor
- Cairo University
Moyamoya Disease, Intracranial Hemorrhages
5T MRI and Metabolomics-Based Hemorrhage Risk Prediction in Moyamoya Disease
Intracranial hemorrhage is a leading cause of death and disability in patients with moyamoya disease (MMD), yet clinically available tools for predicting long-term hemorrhage risk are lacking.
- Conditions
- Moyamoya Disease, Intracranial Hemorrhages, Stroke
- Trial name
- NCT07781579
- Where
- China
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- Beijing Hospital
Arrhythmia
Deep Learning for Intelligent Identification of Arrhythmias
This study aims to design and train a deep learning model for the diagnosis of different arrhythmias.
- Trial name
- ECG-LEARNING (NCT05967546)
- Testing
- Observational
- Where
- China
- Volunteers
- 4,000 people
- Sponsor
- First Affiliated Hospital Xi'an Jiaotong University
Glioma
Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence
This registry aims to collect clinical, molecular and histopathology imaging including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and…
- Trial name
- NCT04215224
- Testing
- Histopathology images based survival prediction for glioma patients
- Where
- China
- Volunteers
- 3,500 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Lymph Nodes With Tumor Metastasis
Predicting Tumor Origin Based on Deep Learning of Lymph Node Puncture Cytology
In this study, the investigators aimed to construct a deep learning diagnostic model that uses cytological images to predict primary unknown tumor origins in patients with tumors combined with lymph node metastases.
- Trial name
- NCT06810349
- Where
- China
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- West China Hospital
Bone Marrow Transplantation, AML
Model-Informed Precision Dosing on Cyclosporine Therapy in Hematopoietic Stem Cell Transplant Recipients
The purpose of this study is to develop a new tool that helps doctors choose the right cyclosporine dose for patients undergoing bone marrow transplantation.
- Trial name
- NCT07695571
- Volunteers
- 300 people
- Sponsor
- Yasmin medhat munir Mohamed
Clear Cell Renal Cell Carcinoma, Prognostic Cancer Model
Contrast-enhanced CT-based Deep Learning Model for Preoperative Prediction of Disease-free Survival (DFS) in Localized Clear Cell Renal Cell Carcinoma (ccRCC)
This study aims to preoperatively predict DFS of patients with localised ccRCC using a deep learning prognostic model based on enhanced contrast CT images, validate it's predictive ability in multicentre data and compare it's…
- Conditions
- Clear Cell Renal Cell Carcinoma, Prognostic Cancer Model, Recurrent Renal Cell Cancer
- Trial name
- NCT06088134
- Where
- China
- Volunteers
- 800 people
- Sponsor
- Mingzhao Xiao
Otalgia, Otitis Media
Validating and AI Software for Assessment of Children With Ear Concerns
The goal of this observational study is to determine if the Glimpse machine learning algorithm can accurately assess ear diseases in children.
- Conditions
- Otalgia, Otitis Media, Otitis Media Effusion
- Trial name
- NCT07243093
- Volunteers
- 658 people
- Sponsor
- Glimpse Diagnostics, Inc.
Pediatric Obstructive Sleep Apnea, Polysomnography
Development of a Multimodal Deep Learning Model for Pediatric Patients
This study aims to develop a multimodal data-driven model integrating multiple noninvasive physiological signals to assess the severity of pediatric sleep-disordered breathing, using standard clinical sleep study results as the…
- Trial name
- NCT07805486
- Testing
- fingertip pulse oximeter, pressure-sensing mattresses, millimeter-wave radar
- Where
- Taiwan
- Volunteers
- 50 people
- Sponsor
- Fu Jen Catholic University
Stroke Outcome Prediction Supported by Deep Learning Algorithm
STOP-stroke: STroke Outcome Prediction in the Acute Treatment Setting
The STOP-stroke project aims at improving prediction of outcome early after stroke. In order to achieve this, we need to understand reasons (important variables) for prediction in a real clinical prognostication process.
- Trial name
- STOP-STroke (NCT06534645)
- Where
- Switzerland
- Volunteers
- 250 people
- Sponsor
- University of Zurich
Tumor
Clinical Application Value of Deep Learning-Based "Opportunistic Screening" for Malignant Tumors on Routine Non-Contrast Chest-Abdomen-Pelvis CT
This study aims to develop and validate a deep learning-based opportunistic multi-cancer screening system using routine non-contrast chest-abdomen-pelvis CT examinations, including CHANCE-Breast, CHANCE-Liver, CHANCE-Kidney, and…
- Trial name
- NCT07639567
- Where
- China
- Volunteers
- 100,000 people, healthy volunteers welcome
- Sponsor
- Lian Yang
BIS, BIS-EEG
Deep Learning Framework for Continuous Depth of Anesthesia Forecasting
The integration of Artificial Intelligence (AI) in anesthesiology offers the potential to shift patient monitoring from reactive to predictive.
- Conditions
- BIS, BIS-EEG, Artifical Intelligence, Intraoperative
- Trial name
- NCT07536230
- Where
- Belgium
- Volunteers
- 115 people, healthy volunteers welcome
- Sponsor
- Universitair Ziekenhuis Brussel
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