Clinical trials: Deep Learning
Abdominal Aortic Aneurysm
Deep Learning Applied to Plain Abdominal Radiographic Surveillance After Endovascular Aneurysm Repair (EVAR) of Abdominal Aortic Aneurysm (AAA)
Deep learning applied to plain abdominal radiographic surveillance after Endovascular Aneurysm Repair (EVAR) of Abdominal Aortic Aneurysm (AAA).
- Trial name
- DeepLearn (NCT04503226)
- Where
- United Kingdom
- Volunteers
- 800 people
- Sponsor
- Liverpool University Hospitals NHS Foundation Trust
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
Cancer Diagnosis, Liver Cancer, Adult
Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening.
- Conditions
- Cancer Diagnosis, Liver Cancer, Adult, Cancer Screening, Colorectal Cancer (CRC)
- Trial name
- NCT06822413
- Testing
- No Interventions
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Optic Neuropathy, Optic Neuropathy, Ischemic
Building Research With Artificial Intelligence in Neuro-Ophthalmology
The research team, recognized as a world leader in Artificial Intelligence for neuro-ophthalmology, has shown that it is possible to diagnose certain neuro-ophthalmologic or neurologic disorders from a single retinal fundus image…
- Conditions
- Optic Neuropathy, Optic Neuropathy, Ischemic, Optic Neuritis, Optic Nerve Diseases
- Trial name
- BRAIN (NCT06390579)
- Testing
- Deep learning algorithm applied on retrospectively collected color fundus photographs
- Where
- France
- Volunteers
- 693 people
- Sponsor
- Fondation Ophtalmologique Adolphe de Rothschild
PechaKucha Presentation, Traditional PowerPoint Presentation
Effect of PechaKucha (PK)Presentation Method on Nursing Students' Satisfaction Level With Deep Breathing and Cough Exercise Skills and Education Method
ABSTRACT Aim: The aim of this study is to examine the effect of the PK presentation method on nursing students' deep breathing and cough exercise skills and the students' level of satisfaction with this method.
- Trial name
- NCT06862024
- Testing
- Deep Breathing and Cough Exercise Skills, Satisfaction with the training method
- Where
- Turkey (Türkiye)
- Volunteers
- 96 people, healthy volunteers welcome
- Sponsor
- Eastern Mediterranean 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
Osteogenic Sarcoma
Accuracy of Deep-learning Algorithm for Detection and Risk Stratification of Lung Nodules
Osteosarcoma is regarded as most common malignant bone tumor in children and adolescents. Approximately 15% to 20% of patients with osteosarcoma present with detectable metastatic disease, and the majority of whom (85%) have…
- Trial name
- NCT04022512
- Testing
- computed tomography
- Where
- Hong Kong
- Volunteers
- 100 people
- Sponsor
- Chinese University of Hong Kong
Labrum Injury of the Hip Joint
Research on Acetabular Labrum Injury Based on MR: Multi-angle Deep Learning Model
The purpose of this study is to study the MRI images of acetabular labrum injury by deep learning method, and try to establish a combination model of axial and coronal serial images, and compare with the diagnostic accuracy of…
- Trial name
- NCT04950036
- Testing
- Diagnostic Test
- Where
- China
- Volunteers
- 1,261 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Breast Cancer Related Lymphedema, Deep Learning
Study on Classification Method of Indocyanine Green Lymphography Based on Deep Learning
Breast cancer related lymphedema (BCRL) is the most common complication after breast cancer surgery, which brings a heavy psychological and spiritual burden to patients.
- Trial name
- BCRL；ICG (NCT04824378)
- Testing
- No Intervention.
- Where
- China
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital
Age-Related Macular Degeneration
Deciphering AMD by Deep Phenotyping and Machine Learning- Prospective Study - SUMMIT (Part 2)
We will conduct a prospective, non-interventional roll-over extension of the PINNACLE study (Deciphering AMD by deep phenotyping and machine learning).
- Trial name
- NCT06682455
- Where
- 8 sites in Austria, United Kingdom
- Volunteers
- 300 people
- Sponsor
- University of Southampton
Fractures, Musculoskeletal
Enhancing Diagnostic Accuracy in Fracture Identification on Musculoskeletal Radiographs Using Deep Learning
This retrospective study aims to evaluate the effectiveness of artificial intelligence (AI) in identifying fractures on musculoskeletal X-rays.
- Trial name
- NCT06644391
- Testing
- Carebot AI Bones
- Where
- Czechia
- Volunteers
- 600 people
- Sponsor
- Carebot s.r.o.
Atrial Fibrillation (AF), Ischemic Stroke
Prediction of Stroke Risk in Patients with Atrial Fibrillation Based on Chest CT Images
This study aims to create and assess a deep learning framework for extracting left atrial appendage features in atrial fibrillation patients and combining them with clinical data to predict ischemic stroke risk.
- Trial name
- NCT06611995
- Testing
- observational study
- Where
- China
- Volunteers
- 1,500 people
- Sponsor
- First Affiliated Hospital of Zhejiang University
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
Otitis Media Acute
Clinical Development of Deep Learning for the OtoSight
The objective of this study is to clinically develop and evaluate a machine learning approach to improve the performance and data interpretation of the PhotoniCare OtoSight Middle Ear Scope in pediatric patients presenting at the…
- Trial name
- NCT04722770
- Testing
- PhotoniCare OtoSight Middle Ear Scope
- Where
- United States
- Volunteers
- 188 people, healthy volunteers welcome
- Sponsor
- PhotoniCare, Inc.
Radiomics, Deep Learning
Retrospective Analysis of the Correlation Between Imaging Features and Pathology, Prognosis in Renal Tumors
Renal cell carcinoma (RCC) is the most common malignant tumor in the kidney with a high mortality rate. Traditional imaging techniques are limited in capturing the internal heterogeneity of the tumor.
- Conditions
- Radiomics, Deep Learning, Artificial Intelligence, Body Composition
- Trial name
- NCT06167863
- Testing
- radiomics
- Where
- China
- Volunteers
- 1,000 people
- Sponsor
- Zhen Li
Acute Appendicitis
IA Model for Acute Appendicitis in CT
the investigators's study group has developed a fully automated 3D convolutional neural network (CNN)-based diagnostic framework using information of appendix (IA) model to identify non-appendicitis and simple and complicated…
- Trial name
- NCT06175169
- Testing
- Information of Appendix (IA) model
- Where
- South Korea
- Volunteers
- 568 people
- Sponsor
- Hallym University Medical Center
Chronic Pancreatitis, Exocrine Pancreatic Insufficiency
AI Evaluation of Pancreatic Exocrine Insufficiency in CP Patients
Early assessment of pancreatic exocrine insufficiency (PEI) is crucial for determining appropriate chronic pancreatitis (CP) treatment plans, thereby avoiding unnecessary suffering and further complications in patients.
- Conditions
- Chronic Pancreatitis, Exocrine Pancreatic Insufficiency, Machine Learning, Deep Learning
- Trial name
- NCT06278272
- Where
- China
- Volunteers
- 504 people
- Sponsor
- Changhai Hospital
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
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
Orthognathic Surgery, Dentofacial Deformities
Development and Validation of an Automated Three-dimensional Cephalometry Method
This study is aimed to develop and assess the validity of an algorithm for automated three-dimensional cephalometry.
- Trial name
- AutoCEPH-3D (NCT04464252)
- Where
- France
- Volunteers
- 453 people
- Sponsor
- Assistance Publique - Hôpitaux de Paris