Clinical trials: Artificial Neural Network
Gross Motor Development Delay
Video-based Assessment of Preschool Children's Gross Motor Development
Artificial intelligence (AI) is currently one of the global focal points for industrial development, with its applications in healthcare steadily increasing, such as in disease prediction, image diagnosis, and drug development.
- Trial name
- NCT07054437
- Testing
- Gross Motor Development Screening Tool
- Where
- Taiwan
- Volunteers
- 250 people
- Sponsor
- Chang Gung Memorial Hospital
Pancreatic Ductal Adenocarcinoma, Pancreatitis, Chronic
Artificial Intelligence in EUS for Diagnosing Pancreatic Solid Lesions
We aim to develop an EUS-AI model which can facilitate clinical diagnosis by analyzing EUS pictures and clinical parameters of patients.
- Conditions
- Pancreatic Ductal Adenocarcinoma, Pancreatitis, Chronic, Pancreatic Neuroendocrine Tumor, Autoimmune Pancreatitis
- Trial name
- NCT05476978
- Testing
- EUS-AI model
- Where
- China
- Volunteers
- 130 people
- Sponsor
- Huazhong University of Science and Technology
Sleep Apnea
Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea
The investigators have developed a simple, accurate, and a point-of-care, computer-based clinical decision support system (CDSS) not only to detect the presence of sleep apnea but also to predict its severity.
- Trial name
- NCT01286636
- Testing
- computer model, Polysomnogram
- Where
- United States
- Sponsor
- State University of New York at Buffalo
COVID19
Evaluation of the AudibleHealth Dx AI/ML-Based Dx SaMD Using FCV-SDS in the Diagnosis of COVID-19 Illness
The AudibleHealth Dx is a diagnostic software as a medical device (Dx SaMD) consisting of an ensemble of software subroutines that interacts with a proprietary database of Signal Data Signatures (SDS), using Artificial…
- Trial name
- NCT05175690
- Testing
- Diagnostic Software as Medical Device
- Where
- United States
- Volunteers
- 1,126 people, healthy volunteers welcome
- Sponsor
- AudibleHealth AI, Inc.
Cardiac Disease
A Study of a Multi-Modal Sensor Patch for Real-Time Physiological Monitoring and Inference
The purpose of this research is to validate the prototype AI-Flex device. Researchers at Mayo Clinic developed a new a flexible multi-modal bio-sensing device, AI-Flex, with integrated artificial intelligence (AI) capability.
- Trial name
- NCT05581290
- Testing
- AI-Flex
- Where
- United States
- Volunteers
- 19 people
- Sponsor
- Mayo Clinic
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
Hypospadias
Identification of Hypospadias Parameters Using Digital Photography and Artificial Intelligence
The goal of this observational study is to develop and validate a digital pattern recognition system based on artificial neural network to determine various parameters in hypospadias.
- Trial name
- ASHOKA (NCT05569863)
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Universitas Indonesia
Basal Cell Carcinoma
AI-Based Risk Classification and Histopathological Subtype Prediction of Basal Cell Carcinoma Using Dermoscopic Images
This retrospective observational study aims to develop and evaluate a convolutional neural network (CNN)-based artificial intelligence model for risk classification and histopathological subtype prediction of basal cell carcinoma…
- Trial name
- BCC-AI (NCT07677124)
- Where
- Turkey (Türkiye)
- Volunteers
- 2,500 people
- Sponsor
- Istanbul Training and Research Hospital
Diabetic Retinopathy, Glaucoma
AI for the Detection of Retinal Disease and Glaucoma in Patients With Diabetes Mellitus in Primary Care
Background: Diabetic retinopathy (DR) is one of the most important causes of blindness worldwide, especially in developed countries.
- Conditions
- Diabetic Retinopathy, Glaucoma, Age-Related Macular Degeneration, Choroidal Nevus
- Trial name
- NCT04132401
- Testing
- algorithm
- Where
- Spain
- Volunteers
- 902 people
- Sponsor
- Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina
High-Risk Multidisciplinary Care, Clinical Decision Support
ANCHOR Validation Trial in High-Risk Multidisciplinary Care
This pre-registered, pragmatic, three-arm (1:1:1) patient-level randomized controlled trial with mixed-effects analysis at the encounter level tests two questions in real high-risk multidisciplinary clinical encounters at the…
- Conditions
- High-Risk Multidisciplinary Care, Clinical Decision Support, Artificial Intelligence-Assisted Care, Telemedicine
- Trial name
- NCT07597499
- Testing
- Gemini 3.1 Pro with Safety Prompt, ANCHOR Clinical AI Verification Layer (with Gemini 3.1 Pro)
- Where
- United States
- Volunteers
- 240 people
- Sponsor
- Waymark
Glaucoma, Tomography, Optical Coherence
The Diagnostic Performance of BMO-MRW and RNFL Thickness and Their Combinational Index Using Artificial Neural Network
This study evaluates the relationship between BMO-MRW and RNFL thickness measured by OCT. SD-OCT exam will be performed to all patients in this study.
- Trial name
- NCT03257020
- Testing
- SD-OCT
- Where
- South Korea
- Volunteers
- 402 people
- Sponsor
- Pusan National University Hospital
Oxidative Injury, Stress Physiological
TORNADO-Omics Techniques and Neural Networks for the Development of Predictive Risk Models
The goal of this observational study is to define a personalized risk model in the super healthy and homogeneous population of Italian Air Force high-performance pilots.
- Conditions
- Oxidative Injury, Stress Physiological, Discogenic Pain, Cardiovascular Risk Factor
- Trial name
- NCT06372054
- Testing
- Biological sample collection
- Where
- Italy
- Volunteers
- 200 people
- Sponsor
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
Hyperkalemia
A Study to Detect Hyperkalemia Using Smartphone-enabled Electrocardiogram (EKG)
The purpose of this study is to validate the real-world performance of a previously developed Artificial Intelligence - Electrocardiogram (AI-ECG) algorithm for identification of hyperkalemia with a six-lead mobile-enhanced…
- Trial name
- REACT (NCT05441852)
- Where
- United States
- Volunteers
- 1,151 people
- Sponsor
- Mayo Clinic
Pneumonia
An Observational Clinical Study on the Construction of an Artificial Neural Network Model for ICU Pneumonia
To achieve rapid, intelligent and accurate microbiological diagnosis and treatment for ICU pneumonia, an artificial neural network model for microbiological diagnosis is established, which depends on many clinical cases and…
- Trial name
- NCT06661499
- Testing
- establish an artificial neural network model
- Where
- China
- Volunteers
- 600 people
- Sponsor
- Chinese Medical Association
MDR Tuberculosis, Resistance to Tuberculostatic Drugs
Artificial Inteligent for Diagnosing Drug-Resistant Tuberculosis
Title: Artificial Neural Network as Diagnostic Tools For Rifampicin-Resistant Tuberculosis In Indonesia. A Predictive Model Study and Economic Evaluation.
- Trial name
- NCT04208789
- Testing
- Rapid Molecular Drug-Resistant Tuberculosis Test, Artificial Intelligent Model, Drug Susceptibility Test
- Where
- 5 sites in Indonesia
- Volunteers
- 524 people
- Sponsor
- Hasanuddin University
Slippery Pulse
Visualization Engineering Platform for Pulse Diagnosis of Traditional Chinese Medicine-The Research of Similar Moiré Feature Analyzing Approach Based on Recurrent Neural Network to Process the Measured Slip Pulse Wave-Images With Chun, Guan and Chy
The diagnoses processes of Traditional Chinese Medicine (TCM) focus on the following four main types of diagnoses methods consisting of inspection, olfaction, inquiry, and palpation.
- Trial name
- NCT04661605
- Testing
- Recurrent Neural Network
- Where
- Taiwan
- Volunteers
- 80 people, healthy volunteers welcome
- Sponsor
- China Medical University Hospital
Pain
The Evaluation With Artificial Neural Network of Pain Scales in Children (ANN)
The study evaluates with Artificial Neural Network (ANN) of pain scales in children. Pain of these patients' will be evaluated by many pain scales in the postoperative period.
- Trial name
- ANN (NCT02682875)
- Where
- Turkey (Türkiye)
- Volunteers
- 140 people, healthy volunteers welcome
- Sponsor
- Cukurova University
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
Lung Diseases, Lung Neoplasm
The Use of Artificial Intelligence to Predict Cancerous Lymph Nodes for Lung Cancer Staging During Ultrasound Imaging
This study aims to determine if a deep neural artificial intelligence (AI) network (NeuralSeg) can learn how to assign the Canada Lymph Node Score to lymph nodes examined by endobronchial ultrasound transbronchial needle…
- Trial name
- NCT03849040
- Testing
- Endobronchial Ultrasound
- Where
- Canada
- Volunteers
- 52 people
- Sponsor
- St. Joseph's Healthcare Hamilton
Pulmonary Hypertension (Diagnosis)
Applying Artificial Intelligence to the 12 Lead ECG for the Diagnosis of Pulmonary Hypertension: an Observational Study
The goal of this observational study is to apply Artificial Intelligence (AI) and machine learning technology to the resting 12-lead electrocardiogram (ECG) and assess whether it can assist doctors in the early diagnosis of…
- Trial name
- NCT05942859
- Testing
- Artificial Intelligence and Machine Learning technology
- Where
- United Kingdom
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Royal United Hospitals Bath NHS Foundation Trust