Clinical trials: Deep Neural Network
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
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
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
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
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
Gastrointestinal Disease
Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases
The purpose of this study is to develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic…
- Trial name
- NCT04222439
- Testing
- AI for the Diagnosis of Gastrointestinal Diseases
- Where
- China
- Volunteers
- 100,000 people, healthy volunteers welcome
- Sponsor
- Shandong University
Gait Disorders, Neurologic, Artificial Intelligence
Deep Neural Network for Stroke Patient Gait Analysis and Classification
Lower limbs of stroke patients gradually recover through Brunnstrom stages, from initial flaccid status to gradually increased spasticity, and eventually decreased spasticitiy. Throughout this process.
- Trial name
- NCT04968418
- Testing
- APDM OPAL system wearable IMU
- Where
- Taiwan
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Cheng-Hsin General Hospital
Valvular Heart Disease
Evaluation of an Automated Smartphone-based Digital Auscultation Application for Detecting Abnormal Heart Sounds Using Deep Learning Techniques
This pilot study is to investigate the feasibility of obtaining medical grade audio phonocardiogram (PCG) recordings using a smartphone-based auscultation device in the first step.
- Trial name
- AVDA (NCT05325723)
- Where
- Switzerland
- Volunteers
- 102 people, healthy volunteers welcome
- Sponsor
- University Hospital, Basel, Switzerland
Diabetes
Validation of the Diabetes Deep Neural Network Score for Diabetes Mellitus Screening
The Validation of the Diabetes Deep Neural Network Score (DNN score) for Screening for Type 2 Diabetes Mellitus (diabetes) is a single center, unblinded, observational study to clinically validating a previously developed remote…
- Trial name
- NCT05303051
- Testing
- Application Validation
- Where
- United States
- Volunteers
- healthy volunteers welcome
- Sponsor
- University of California, San Francisco
Ophthalmological Disorder, Image, Body
Explainable Ocular Fundus Diseases Report Generation System
To establish a deep learning system of various ocular fundus disease analytics based on the results of multimodal examination images.
- Trial name
- NCT05622565
- Testing
- Various modalities of ocular fundus imaging
- Where
- China
- Volunteers
- 15,000 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University
PET Images and Deep Neural Networks Algorithms
Positron Emission Tomography (PET) Images Using Deep Neural Networks
PET images are based on detecting two annihilation 511 KeV photons that are produced by positron emitting isotopes. The longer the acquisition time, the more photons are detected and processed, resulting in better image quality.
- Trial name
- NCT04140565
- Where
- Israel
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Sheba Medical Center
Posterior Chamber Phakic Intraocular Lens, Vault
Study on the Diagnostic Efficacy of ICL Selection and Prediction Depth Model Based on Eye Images
To evaluate the diagnostic efficacy of deep learning network model in implantable collamer lens selection and prediction in a multicenter cross-sectional study
- Conditions
- Posterior Chamber Phakic Intraocular Lens, Vault, Deep Neural Network, Myopia
- Trial name
- NCT06669728
- Testing
- AI diagnostic algorithm
- Where
- China
- Volunteers
- 326 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
Sleep Apnea Syndrome, Obstructive, Drowsiness
Ocular Parameters in Patients With Sleep Apnea
The aim of this study is to assess the ocular parameters of drowsiness in patients with diagnosed Obstructive Sleep Apnea Syndrome through objective methods of ocular imaging and subjective evaluation methods (questionnaire)
- Conditions
- Sleep Apnea Syndrome, Obstructive, Drowsiness, Blinking, Concentration Ability Impaired
- Trial name
- NCT05911737
- Testing
- Short video and Questionnaire
- Where
- Greece
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Democritus University of Thrace
COVID-19
Classification of COVID-19 Infection in Posteroanterior Chest X-rays
The objective of this study is to assess three configurations of two convolutional deep neural network architectures for the classification of COVID-19 PCX images.
- Trial name
- NCT04358536
- Testing
- CovX
- Where
- United States
- Volunteers
- 230 people, healthy volunteers welcome
- Sponsor
- Dascena
AKI
Deep Learning Model and Risk Factors for Tacrolimus-related Acute Kidney Injury
In this study, the investigators aim to develop a risk prediction model for acute kidney injury (AKI) in hospitalized patients using the calcineurin inhibitor tacrolimus.
- Trial name
- NCT06596798
- Where
- China
- Volunteers
- 1,200 people, healthy volunteers welcome
- Sponsor
- Qianfoshan Hospital
Robot Surgery
Transfer Learning of a Neural Network for Robotic Surgical Assessment
The goal of this observational study is to explore how pretrained artificial intelligence (AI) models, trained on preclinical data, can improve the accuracy of action recognition and skills assessment in robot-assisted surgery…
- Trial name
- NCT06612606
- Testing
- observational study
- Where
- Denmark
- Volunteers
- 5 people, healthy volunteers welcome
- Sponsor
- Aalborg University