Clinical trials: Learning Model, open to volunteers
Intracranial Aneurysm
Placental Learning Model for Neurovascular Microsurgery for the Management of Intracranial Aneurysms
Training in microsurgical techniques for the management of intracranial aneurysms is carried out during the practical training of the DES in Neurosurgery and during the continuous training of neurosurgeons according to the…
- Trial name
- NeuroVasc (NCT06117527)
- Where
- France
- Volunteers
- 50 people
- Sponsor
- University Hospital, Strasbourg, France
Chronic Kidney Disease, Type 2 Diabetes Mellitus
An Observational Study, Called FINEXPLORER, to Learn More About How Well Finerenone Works in Adults in Spain With Chronic Kidney Disease (CKD) Linked to Type 2 Diabetes, by Looking at Changes in a CKD Risk Score
This is a prospective observational study in which data from people with chronic kidney disease (CKD) associated with type 2 diabetes (T2D) who will be receiving finerenone are collected and analyzed.
- Trial name
- FINEXPLORER (NCT07554469)
- Testing
- Finerenone (Kerendia, BAY94-8862)
- Where
- Spain
- Volunteers
- 500 people
- Sponsor
- Bayer
Colonoscopy
External, Multicentre Validation of a Machine-Learning Model to Predict Colonic Adenoma in Indian Adults
Colorectal adenomas are precursors to colorectal cancer (CRC). Accurate pre-procedure risk stratification could optimize colonoscopy yield and resource allocation in India, where adenoma prevalence varies by age, sex, and…
- Trial name
- NCT07329816
- Testing
- Not Applicable / Observational study
- Volunteers
- 1,000 people
- Sponsor
- Asian Institute of Gastroenterology, India
Health Belief Model-Based Osteoporosis Education Programme
OSTEOPOROSIS EDUCATION AND ITS IMPACT ON OSTEOPOROSIS HEALTH BELIEFS AND AWARENESS IN WOMEN AT RISK OF OSTEOPOROSIS
Osteoporosis is a significant public health problem characterized by low bone mass and deterioration in the microarchitecture of bone tissue, leading to an increased risk of fractures.
- Trial name
- HBM-osteo-edu (NCT07486076)
- Testing
- Osteoporosis Education Based on the Health Belief Model
- Where
- Turkey (Türkiye)
- Volunteers
- 74 people, healthy volunteers welcome
- Sponsor
- Bartın Unıversity
Chronic Disease, Risk Assessment
Adult Disease Risk Prediction Using Wearables, Hearing, and Health Data
This prospective cohort study aims to develop and validate a personalized disease risk prediction model for adults by integrating multiple sources of health data.
- Trial name
- NCT07541547
- Where
- Taiwan
- Volunteers
- 1,500 people, healthy volunteers welcome
- Sponsor
- National Health Research Institutes, Taiwan
Asthma (Diagnosis)
Resources and Education for Addressing Chronic Health (REACH)
This study pilots REACH, Resources and Education for Addressing Chronic Health, a service model to facilitate care coordination and communication across medical, school, and home settings.
- Trial name
- REACH (NCT07819747)
- Testing
- REACH
- Where
- United States
- Volunteers
- 430 people
- Sponsor
- Washington University School of Medicine
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
Bone Aging, Osteoporosis Diagnosis
Automated Bone Age Estimation From Noncontrast Abdominal CT Using Deep Learning
This study is a retrospective analysis that uses abdominal CT scans, which were originally taken for other medical reasons, to estimate bone age.
- Trial name
- NCT07162168
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital
Hepatecellular Carcinoma, Hepatectomy
AI-Based Prediction of HCC Recurrence Patterns After Resection (APAR)
This observational study aims to validate a deep learning model for predicting aggressive recurrence patterns in patients with early-stage liver cancer (HCC) after surgery.
- Trial name
- NCT07062380
- Testing
- Curative liver resection, Real-world multimodal therapy
- Where
- China
- Volunteers
- 353 people
- Sponsor
- Tongji Hospital
HCC
Efficacy and Safety of Neoadjuvant Therapy in Patients With Resectable HCC Screened by a Multimodal Deep Learning Model.
Primary liver cancer is one of the most common malignant tumors in the world, and more than 90% of primary liver cancers are pathologically characterized as hepatocellular carcinoma (HCC).
- Trial name
- NCT06311916
- Testing
- HAIC + Tirelizumab +lenvatinib +liver resection, liver resection
- Volunteers
- 312 people
- Sponsor
- Chen Xiaoping
Temperature Change, Body, Emergency Department Visit
Performance Study of the Thermodiag Solution for Body Temperature Measurement
The goal of this prospective, comparative, multi-centre interventional clinical investigation, is to evaluate the performance of the Thermodiag® medical device, compared with reference methods, for continuous measurement of core…
- Trial name
- ThermodiagPERF (NCT06703931)
- Testing
- Measures performed on all subjects
- Where
- 4 sites in France
- Volunteers
- 60 people
- Sponsor
- F2D Medical
Breast Cancer, Benign Breast Condition
ATUSA Ultrasound Diagnostic Imaging for Breast Lesions Evaluation (AUDIBLE) - iSono Health
AUDIBLE is a multi-site, clinical study conducted in the United States aimed at gathering data on 3D Automated Breast Ultrasound imaging using the iSono Health ATUSA system.
- Conditions
- Breast Cancer, Benign Breast Condition, Breast Fibroadenoma, Breast Neoplasms
- Trial name
- AUDIBLE (NCT07505797)
- Testing
- ATUSA 3D Automated Breast Ultrasound System
- Where
- 2 sites in United States
- Volunteers
- 800 people
- Sponsor
- iSono Health, Inc.
Deep Learning, Head & Neck Squamous Cell Carcinoma
A Bidirectional Study of Individualized Postoperative Adjuvant Treatment Decision Model for Locally Advanced Head and Neck Squamous Cell Carcinoma Based on Multimodal Dynamic Data
Based on multimodal data, the investigators establish a dynamic deep learning model to conduct prognostic risk assessment for patients and recommend the 'most suitable' treatment/follow-up regimen after radical treatment…
- Trial name
- NCT07532928
- Where
- China
- Volunteers
- 571 people
- Sponsor
- Nanfang Hospital, Southern Medical University
Cardiac Arrhythmias, Acute Myocardial Infarction (AMI)
Predict Arrhythmia Risk Using Intelligent Software
Cardiac arrhythmias frequently occur in patients admitted to the Coronary Care Unit (CCU). The majority of these patients are treated for an acute myocardial infarction, which carries an increased risk of life-threatening…
- Conditions
- Cardiac Arrhythmias, Acute Myocardial Infarction (AMI), Ventricular Tachycardia (VT), Ventricular Fibrillation
- Trial name
- PARIS (NCT07792694)
- Where
- Netherlands
- Volunteers
- 3,000 people
- Sponsor
- Catharina Ziekenhuis Eindhoven
Kawasaki Disease, Chest X-ray for Clinical Evaluation
Clinical Study on an Artificial Intelligence-Assisted Chest Radiograph Model Based on Big Data and Deep Learning for Early Detection of Kawasaki Disease
The goal of this observational study is to develop an AI-based early warning system for Kawasaki Disease (KD) using chest X-rays (CXR) in children diagnosed with Kawasaki Disease. The main question[s] it aims to answer are: 1.
- Conditions
- Kawasaki Disease, Chest X-ray for Clinical Evaluation, Mucocutaneous Lymph Node Syndrome
- Trial name
- NCT07405658
- Testing
- AI-Based Early Warning System for Kawasaki Disease
- Where
- China
- Volunteers
- 20,000 people, healthy volunteers welcome
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Prenatal Education Program, Indivisible Self Model
The Psychosocial Effects of Prenatal Education With the Indivisible Self Model
This study was designed to compare the effects of a prenatal education program based on the Indivisible Self Model with those of a needs-based prenatal education program on psychosocial outcomes among pregnant women.
- Conditions
- Prenatal Education Program, Indivisible Self Model, Salutogenic Approach
- Trial name
- NCT07699900
- Testing
- Prenatal Education Program Based on the Indivisible Self Model, The needs-based prenatal education program
- Volunteers
- 76 people, healthy volunteers welcome
- Sponsor
- Mersin University
Anxiety, Episiotomy
Video-Supported Flipped Learning for Episiotomy Training in Midwifery Students
This study aims to evaluate the effect of a video-supported flipped learning model on anxiety and skill levels of midwifery students in episiotomy education.
- Conditions
- Anxiety, Episiotomy, Midwifery, Clinical Competence
- Trial name
- NCT07530692
- Testing
- Video-Supported Flipped Learning Model
- Volunteers
- 60 people, healthy volunteers welcome
- Sponsor
- Karabuk University
Breast Cancer
Artificial Intelligence and Machine Learning to Guide CDK4/6 Inhibitor Rechallenge in Breast Cancer.
The goal of this clinical trial is to learn if an artificial intelligence model will be able to select patients with advanced breast cancer who may respond to a second cyclin-dependent kinase 4/6 (CDK4/6) inhibitor after they…
- Trial name
- AIM-BRIGHT (NCT07227233)
- Testing
- A CDK4/6 inhibitor different from the first that the participant had received, plus fulvestrant., Treatment of physician's choice
- Where
- United States
- Volunteers
- 105 people
- Sponsor
- University of California, San Diego
Acute Myocardial Infarction, Cardiac Rehabilitation
Effect of Digital Therapeutics for Cardiac Rehabilitation in Patients With Acute Myocardial Infarction
This study adopts a multicenter, open-label, randomized controlled clinical study, with Jiangsu Provincial People's Hospital as the leading unit, and the other 13 hospitals as cooperative units.
- Trial name
- NCT06772337
- Testing
- digital cardiac rehabilitation, Regular Treatment
- Where
- China
- Volunteers
- 160 people
- Sponsor
- The First Affiliated Hospital with Nanjing Medical University
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