Clinical trials: Deep Neural Network
Knee Osteoarthritis, Total Knee Arthroplasty
Prediction of Postoperative Outcomes After TKA Using Instrumented Insoles and DNN
This multicenter prospective observational study aims to evaluate whether preoperative clinical variables and wearable sensor-derived gait features can predict postoperative improvement after total knee arthroplasty (TKA).
- Trial name
- NCT07367789
- Testing
- Instrumented Insole Gait Assessment
- Where
- South Korea
- Volunteers
- 200 people
- Sponsor
- Yonsei University
Cervical Myelopathy
Convolutional Neural Network for the Detection of Cervical Myelomalacia
Deep learning technology has been used increasingly in spine surgery as well as in many medical fields. However, it is noticed that most of the studies about this subject in the literature have been conducted except of the…
- Trial name
- NCT04796987
- Testing
- Convolutional Neural Network
- Where
- Turkey (Türkiye)
- Volunteers
- 125 people
- Sponsor
- Istanbul University
Coronary Artery Disease, Plaque, Atherosclerotic
Identifying Vulnerable CoronAry PLaqUes With Artificial IntElligence-assisted CT Angiography
The goal of this observational study is to develop an automatic whole-process AI model to detect, quantify, and characterize plaques using coronary CT angiography in coronary artery disease patients.
- Trial name
- VALUE (NCT06025305)
- Testing
- Intravascular imaging test, Coronary plaque assessment
- Where
- China
- Volunteers
- 2,000 people
- Sponsor
- Jinling Hospital, China
Artificial Intelligence, Ultrasonography
Assessment of Liver Diseases Using a Deep-Learning Approach Based on Ultrasound RF-Data
The goal of this clinical trial is to test the performance of neuronal networks trained on ultrasonic raw Data (=radiofrequency data) for the assessment of liver diseases in patients undergoing a clinical ultrasound examination.
- Conditions
- Artificial Intelligence, Ultrasonography, Elasticity Imaging Techniques, Liver Diseases
- Trial name
- LivSPECTRUS (NCT06317181)
- Testing
- Collection of elastography data, Collection of ultrasonic raw data
- Where
- 4 sites in Germany
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Technische Universität Dresden
Gingivitis
AI Gum Health Evaluation with Smartphone
Background The most common dental diseases are tooth decay (caries) and gum disease (gingivitis and periodontitis). Obviously, these diseases are caused by dental plaque (bacterial biofilm).
- Trial name
- NCT05685355
- Testing
- Standardized intraoral photography
- Where
- Hong Kong
- Volunteers
- 1,200 people, healthy volunteers welcome
- Sponsor
- The University of Hong Kong
COVID-19 (Coronavirus Disease 2019), COVID-19 Pneumonia
Convolutional Neural Network Model to Detect Coronavirus Disease 2019 (COVID-19) Pneumonia in Chest Radiographs
This study aims to design a Convolutional Neural Network (CNN) and apply an attention model to help differentiate pneumonia due to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pneumonia due to other…
- Trial name
- RedNeumon (NCT05722665)
- Testing
- Categorization of chest xrays images
- Where
- Colombia
- Volunteers
- 3,599 people, healthy volunteers welcome
- Sponsor
- Fundacion Clinica Valle del Lili
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
Congenital Microtia
Deep Learning for Flap Perfusion Detection
The aim of this study is to develop a convolutional neural network-based image recognition model to identify flap perfusion abnormalities after first-stage auricular reconstruction in patients with congenital microtia.
- Trial name
- DL-FPA (NCT07846332)
- Testing
- AI-assisted remote monitoring of flap perfusion abnormalities after first-stage auricular reconstruction
- Where
- China
- Volunteers
- 232 people
- Sponsor
- Jing Xu
Dental Prosthesis
Artificial Intelligence Designed Single Tooth Dental Prostheses
Tooth loss is common and as consequence deteriorate patient's health and quality-of-life. Dental prostheses aim to restore patients' appearance and functions by replacement of missing teeth.
- Trial name
- NCT05056948
- Testing
- artificial intelligence (AI) computer assisted design (CAD)
- Where
- Hong Kong
- Volunteers
- 250 people, healthy volunteers welcome
- Sponsor
- The University of Hong Kong
Deep Convolutional Neural Network, Small-incision Lenticule Extraction (SMILE) Surgery
Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE
To evaluate the diagnostic efficiency of the neural network in predicting complications of Small Incision Lenticule Extraction in a multi-center cross-sectional study.
- Conditions
- Deep Convolutional Neural Network, Small-incision Lenticule Extraction (SMILE) Surgery, Intraoperative Complications, Postoperative Outcomes
- Trial name
- NCT06204926
- Testing
- AI diagnostic algorithm
- Where
- China
- Volunteers
- 1,250 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
Feeding and Eating Disorders
A New Neuroregulatory Technology for the Therapy of AN Based on the Pathological Neural Network of ACC
Hypothesis of "AN-ACC pathological network" suggests that ACC overactivation and abnormal functional connectivity with other brain regions is the neuropathological mechanism for the onset of AN.
- Trial name
- NCT06152640
- Testing
- Deep transcranial magnetic stimulation, Basic treatment
- Where
- China
- Volunteers
- 80 people
- Sponsor
- Shanghai Mental Health Center
Diagnositic Efficacy of Deep Convolutional Neural Network in Differentiation of Glaucoma Visual Field From Non-glaucoma Visual Field
Diagnostic Efficacy of CNN in Differentiation of Visual Field
Glaucoma is currently the leading cause of irreversible blindness in the world. The multi-center study is designed to evaluate the efficacy of the convolutional neural network based algorithm in differentiation of glaucomatous…
- Trial name
- NCT03759483
- Testing
- AI diagnostic algorithm
- Where
- China
- Volunteers
- 437 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
Hepatocellular Carcinoma, Chronic Liver Disease
Risk Stratification of Hepatocarcinogenesis Using a Deep Learning Based Clinical, Biological and Ultrasound Model in High-risk Patients
By 2030, hepatocellular carcinoma (HCC) will become the second leading cause of cancer-related death, accounting for more than one million deaths per year according to the World Health Organization.
- Trial name
- STARHE (NCT04802954)
- Testing
- Video acquisition
- Where
- 6 sites in France
- Volunteers
- 400 people
- Sponsor
- IHU Strasbourg
Ultrasound Therapy; Complications
Identification of Interscalene Brachial Plexus on Ultrasonography Using a Deep Neural Network
The purpose of the study is to develop and validate an algorithm based on deep neural networks (DNNs) to identify interscalene brachial plexus on ultrasonography automatically.
- Trial name
- IBRUNNET (NCT04183972)
- Testing
- ultrasound examination
- Where
- China
- Volunteers
- 1,126 people
- Sponsor
- Huashan Hospital
Blinking, Deep Learning
Development and Validation of Deep Neural Networks for Blinking Identification and Classification
Primary objective of this study is the development and validation of a system of deep neural networks which automatically detects and classifies blinks as "complete" or "incomplete" in image sequences.
- Trial name
- NCT04828187
- Testing
- Comparison of the proposed artificial network with the ground truth
- Where
- 2 sites in Greece
- Volunteers
- 8 people, healthy volunteers welcome
- Sponsor
- Democritus University of Thrace
Solitary Skin Lesions, Skin Neoplasms
CNN-Based AI Versus Physicians for Solitary Skin Lesion Diagnosis
The goal of this observational study is to evaluate the diagnostic accuracy of a CNN-based artificial intelligence model in patients with solitary skin lesions.
- Conditions
- Solitary Skin Lesions, Skin Neoplasms, Skin Neoplasm Malignant
- Trial name
- NCT07415291
- Where
- Turkey (Türkiye)
- Volunteers
- 17,625 people
- Sponsor
- Istanbul Training and Research Hospital
Femoroacetabular Impingement Syndrome
AI-Based Screening and Diagnostic Models for Femoroacetabular Impingement Syndrome (FAIS-AI)
Femoroacetabular impingement syndrome (FAIS) is the leading cause of hip pain in young adults and frequently progresses to osteoarthritis, often exacerbated by delayed diagnosis in primary care.
- Trial name
- FAIS-AI (NCT07737223)
- Where
- China
- Volunteers
- 2,617 people
- Sponsor
- ChunBao Li
Esophageal Squamous Cell Carcinoma
Accurate Diagnosis of the Invasion Depth in ESCC by a Deep Neural Network Analysis of NBI Endoscopy Data
The goal of this observational study is to accurate diagnose the stage of esophageal squamous cell carcinoma in order to help physicians to decide the appropriate clinical treatment.
- Trial name
- NCT06252974
- Volunteers
- 500 people
- Sponsor
- RenJi Hospital
Hepatocellular Carcinoma (HCC), Radiofrequency Ablation
Ga-68 Dolacga PET Scan in HCC Under RFA
This study aims to investigate the use of Ga-68 Dolacga PET scan technology to assess treatment response and liver function changes in patients of early-stage liver cancer receiving RFA.
- Conditions
- Hepatocellular Carcinoma (HCC), Radiofrequency Ablation, PET Scan, Computed Tomography
- Trial name
- HCC; RFA (NCT06792097)
- Testing
- Ga-68 Dolacga PET scan
- Volunteers
- 10 people
- Sponsor
- National Taiwan University Hospital
Healthy Individual
CDSS-assisted UGI Endoscopy vs. Routine Screening Endoscopy
This study aimed to find the CDSS-assisted upper GI endoscopy has clinical benefit compared to conventional routine screening upper GI endoscopy. Investigators will conduct a pilot randomized controlled study.
- Trial name
- NCT05452473
- Testing
- CDSS-assisted upper GI endoscopy, no intervention
- Where
- South Korea
- Volunteers
- 1,200 people, healthy volunteers welcome
- Sponsor
- Chuncheon Sacred Heart Hospital