Clinical trials: Deep Learning
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
Dental Plaque (Diagnosis), Deep Learning
Microbial Dental Plaque Analysis in Young Permanent Teeth Using Deep Learning
Background: Dental plaque contributes to a number of common oral conditions such as caries, gingivitis, and periodontitis. As a result, detection and management of plaque is of great importance for the oral health of individuals.
- Trial name
- NCT06603233
- Testing
- The Difference Between The AI Model and Dentists Group, Deep Learning Models
- Where
- Turkey (Türkiye)
- Volunteers
- 31 people, healthy volunteers welcome
- Sponsor
- Ankara Medipol University
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
Artificial Intelligence, Electrocardiogram
Artificial Intelligence-enabled ECG Detection of Congenital Heart Disease in Children: a Novel Diagnostic Tool
Congenital heart disease (CHD) is the most common congenital disease in children. The early detection, diagnosis and treatment of CHD in children is of great significance to improve the prognosis and reduce the mortality of…
- Conditions
- Artificial Intelligence, Electrocardiogram, Deep Learning, Congenital Heart Disease in Children
- Trial name
- AI-ECG-CHD (NCT06383546)
- Where
- China
- Volunteers
- healthy volunteers welcome
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
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
Dyspnea
Artificial Intelligence to Improve Physicians' Interpretation of Chest X-Rays in Breathless Patients
Identifying the cause of breathlessness in acute patients in the emergency department is critical and challenging. The chest X-ray is central but challenging to read for non-radiologist physicians.
- Trial name
- XRAI (NCT05117320)
- Testing
- AI support
- Where
- Denmark
- Volunteers
- 33 people, healthy volunteers welcome
- Sponsor
- Bispebjerg Hospital
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
3D-reconstruction, Patient Privacy
Reconstruction Technology to Auxiliary Diagnosis and Guarantee Patient Privacy
Medical data that contain facial images are particularly sensitive as they retain important personal biometric identity, privacy protection.
- Conditions
- 3D-reconstruction, Patient Privacy, Deep Learning, Digital Medicine
- Trial name
- NCT05058599
- Testing
- DM
- Where
- China
- Volunteers
- 400 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Breast Cancer
Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization
The correct categorization of breast density is essential to adapt the diagnostic examination to the needs of each patient. Assessment of breast density is performed visually by radiologists.
- Trial name
- NCT05021055
- Volunteers
- 277 people, healthy volunteers welcome
- Sponsor
- Hospital Italiano de Buenos Aires
Breast Cancer
Artificial Intelligence in Mammography-Based Breast Cancer Screening
Breast cancer (BC) is the most common cancer among women in worldwide and the second leading cause of cancer-related death. As the corner stone of BC screening, mammography is recognized as one of useful imaging modalities to…
- Trial name
- NCT04156880
- Testing
- mammography
- Where
- Hong Kong
- Volunteers
- healthy volunteers welcome
- Sponsor
- Chinese University of Hong Kong
Keratoconus, Eye Diseases
Development of a Keratoconus Detection Algorithm by Deep Learning Analysis and Its Validation on Eyestar Images
Monocentric clinical study to develop an imaging analysis algorithm for the Eyestar 900 to identify keratoconus corneas and improve biometry for intraocular lens calculations
- Conditions
- Keratoconus, Eye Diseases, Cataract, Corneal Ectasia
- Trial name
- DKDA (NCT04763785)
- Testing
- Corneal tomography with Eyestar 900, Corneal tomography with Pentacam, Biometry with IOL-Master
- Where
- Switzerland
- Volunteers
- 4,800 people, healthy volunteers welcome
- Sponsor
- Insel Gruppe AG, University Hospital Bern
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
Testicular Appendix Torsion, Testicular Torsion
Deep Learning-Assisted Ultrasonic Diagnosis and Localization of Testicular Appendix Torsion
Ultrasound data were both retrospectively and prospectively collected from the primary center and six other sub-centers. Combined with clinical diagnostic outcomes, the data labeling was completed by physicians with extensive…
- Conditions
- Testicular Appendix Torsion, Testicular Torsion, Epididymitis
- Trial name
- NCT07301086
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- Ying Jiang
Parkinson Disease, Multiple System Atrophy
Facilitating Diagnostics and Prognostics of Parkinsonian Syndromes Using Neuroimaging
The goals of this study are: 1) to identify biomarkers using neuroimaging that are associated with progression rate using statistical methods, and 2) to identify biomarkers that are associated with the differential diagnosis of…
- Conditions
- Parkinson Disease, Multiple System Atrophy, Progressive Supranuclear Palsy
- Trial name
- NCT03872102
- Where
- United States
- Volunteers
- 90 people, healthy volunteers welcome
- Sponsor
- University of Texas Southwestern Medical Center
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
Ophthalmological Disorder
Development and Validation of a Deep Learning System for Multiple Ocular Fundus Diseases Using Retinal Images
Retinal images can reflect both fundus and systemic conditions (diabetes and cardiovascular disease) and firstly to be used for medical artificial intelligence (AI) algorithm training due to its advantages of clinical…
- Trial name
- NCT04213430
- Testing
- diagnostic
- Where
- China
- Volunteers
- 300,000 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Glioma
Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Artificial Intelligence
This registry aims to collect clinical, molecular and radiologic data including detailed clinical parameters, molecular pathology (1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations, etc) and images of HE slices in…
- Trial name
- NCT04217044
- Testing
- Histopathology images based prediction of molecular pathology
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Androgenetic Alopecia
Harnessing Artificial Intelligence for Diagnosing Androgenetic Alopecia: A Training and Validation Study
The aim of this study is to develop and validate deep learning models in diagnosis of male and female pattern hair loss, and assessment of its severity based on clinical and trichoscopic image by handheld dermoscopy and…
- Trial name
- NCT07294313
- Where
- Egypt
- Volunteers
- 400 people, healthy volunteers welcome
- Sponsor
- Cairo University
Visual Function, Vision
Visual Function Screening System With Special Needs Children and Typical Preschoolers
The early visual screening of children plays a critical role in promoting visual development, especially for those with visual impairments.
- Conditions
- Visual Function, Vision, Special Needs Children
- Trial name
- NCT07081139
- Testing
- observational study, no interventional
- Where
- Taiwan
- Volunteers
- 1,300 people, healthy volunteers welcome
- Sponsor
- National Taiwan University Hospital