Clinical trials: Artificial Neural Network
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
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
Arrhythmias, Cardiac, Cardiac Arrest
Development of a Novel Convolution Neural Network for Arrhythmia Classification
Identifying the correct arrhythmia at the time of a clinic event including cardiac arrest is of high priority to patients, healthcare organizations, and to public health.
- Conditions
- Arrhythmias, Cardiac, Cardiac Arrest, Cardiac Arrythmias
- Trial name
- AI-ECG (NCT03662802)
- Testing
- Neural Network Classifier
- Where
- United States
- Volunteers
- 25,458 people, healthy volunteers welcome
- Sponsor
- Scripps Clinic
Volatile Organic Compounds, Radiography
Tuberculosis Screening in Paraguayan Prisons
Two diagnostic tools for TB screening in high risk groups need additional assessment: the AeoNose™, an 'electronic nose device' for breath sampling, and digital chest X-ray (CXR) with computer aided detection with CAD4TB®…
- Trial name
- Prinose (NCT04407325)
- Testing
- electronic nose device, dig chest Xray with automated readings
- Where
- 2 sites in Paraguay
- Volunteers
- 5,000 people, healthy volunteers welcome
- Sponsor
- Radboud University Medical Center
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