Clinical trials: Deep Neural Network
Intubation, Machine Learning
Prediction of Endotracheal Tube Depth by Using Deep Convolutional Neural Networks
Malposition of an endotracheal tube (ETT) may lead to a great disaster. Developing a handy way to predict the proper depth of ETT fixation is in need.
- Trial name
- NCT05085743
- Testing
- Deep convolutional neural networks analysis
- Where
- Taiwan
- Volunteers
- 595 people
- Sponsor
- Chang Gung Memorial Hospital
Cardiac Arrhythmias, Acute Myocardial Infarction (AMI)
Predict Arrhythmia Risk Using Intelligent Software
Cardiac arrhythmias frequently occur in patients admitted to the Coronary Care Unit (CCU). The majority of these patients are treated for an acute myocardial infarction, which carries an increased risk of life-threatening…
- Conditions
- Cardiac Arrhythmias, Acute Myocardial Infarction (AMI), Ventricular Tachycardia (VT), Ventricular Fibrillation
- Trial name
- PARIS (NCT07792694)
- Where
- Netherlands
- Volunteers
- 3,000 people
- Sponsor
- Catharina Ziekenhuis Eindhoven
Thoracic Diseases, Lung Diseases
AI-Based Assessment of Chest Diseases on Chest X-ray Imaging Using DenseNet-121 and a CheXpert-Trained Model
Chest X-rays are widely used to detect thoracic and lung conditions, but reviewing high volumes of radiographs can lead to workload strain and variation between interpreters.
- Trial name
- NCT07834879
- Volunteers
- 100 people
- Sponsor
- Assiut University
Ulcerative Colitis
Development and Validation of a Deep Learning Algorithm to Evaluate Endoscopic Disease Activity of Ulcerative Colitis.
The purpose of this study is to develop an artificial intelligence(AI) assisted scoring system, which can evaluate the disease severity and mucosal healing stage in patients with ulcerative colitis.
- Trial name
- NCT03973437
- Testing
- Artificial inteligence associated ulcerative colitis severity scoring system, Conventional human scoring
- Where
- China
- Volunteers
- 200 people
- Sponsor
- Shandong University
Parkinson Disease
Deep Neural Network Approaches for Closed-Loop Deep Brain Stimulation
In this research study the researchers want to learn more about brain activity related to speech perception and production in patients with Parkinson's Disease who are undergoing deep brain stimulation (DBS).
- Trial name
- NCT04277689
- Testing
- Brain signal data collection
- Where
- United States
- Sponsor
- Massachusetts General 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
Cardiac Surgical Procedures, Pediatrics
Bayesian Networks in Pediatric Cardiac Surgery
Pediatric cardiac surgery with cardiopulmonary bypass is associated with significant morbidity and mortality. Also score systems for risk factors, such as Risk Adjustment for Congenital Heart surgery (RACHS 1) score or the…
- Conditions
- Cardiac Surgical Procedures, Pediatrics, Cardiopulmonary Bypass
- Trial name
- NCT05537168
- Testing
- Pediatric cardiac surgery under cardiopulmonary bypass
- Where
- Belgium
- Volunteers
- 1,364 people
- Sponsor
- Brugmann University Hospital
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
Pneumoconiosis
Evaluation of Pneumoconiosis High Risk Early Warning Models
Precaution of pneumoconiosis is more important than treatment. However, the current process can't early warn the high-risk dust exposed workers until they are diagnosed with pneumoconiosis.
- Trial name
- NCT04952675
- Where
- China
- Volunteers
- 200 people
- Sponsor
- Peking University Third Hospital
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
Thyroidectomy
DCNN Developed for Detection and Assessing the Perfusion of PTG
Since the anatomical location and appearance of the parathyroid gland (PTG) vary, detection of the PTG and preserving the blood supply are among the difficulties encountered during a thyroidectomy procedure.
- Trial name
- NCT05869058
- Testing
- a deep convolutional neural network
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
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
Polycystic Liver Disease, Polycystic Hepatorenal Disease
Automatic Segmentation of Polycystic Liver
Assessing the volume of the liver before surgery, predicting the volume of liver remaining after surgery, detecting primary or secondary lesions in the liver parenchyma are common applications that require optimal detection of…
- Conditions
- Polycystic Liver Disease, Polycystic Hepatorenal Disease, Liver Injury
- Trial name
- ASEPOL (NCT03960710)
- Testing
- Anonymized CT examinations, Training (1), Training (2)
- Where
- France
- Volunteers
- 120 people
- Sponsor
- Hospices Civils de Lyon
Atrial Fibrillation, Insulin Resistance
Insulin Resistance as a Predictor of Pulsed Field Ablation Success in Atrial Fibrillation (HOMA-PULSE)
This study investigates whether insulin resistance, a metabolic condition where the body's cells respond poorly to insulin, can predict the success of atrial fibrillation (AF) ablation using pulsed field ablation (PFA)…
- Conditions
- Atrial Fibrillation, Insulin Resistance, Catheter Ablation, Artificial Intelligence
- Trial name
- HOMA-PULSE (NCT07551947)
- Where
- Czechia
- Volunteers
- 120 people
- Sponsor
- Nemocnice AGEL Trinec-Podlesi a.s.
Endometriosis
Deep Neural Network Stratification for Use Detecting Endometriosis in Women Affected by Chronic Pelvic Pain (EndoCheck)
The goal of this observational study is to determine the clinical validity of a deep neural network algorithm that utilizes protein biomarker detection of Endometriosis - "EndoCheck" - as an "aid in diagnosis" for endometriosis…
- Trial name
- NCT05245695
- Testing
- Observational study, no intervention
- Where
- 10 sites in United States
- Volunteers
- 1,200 people
- Sponsor
- Aspira Women's Health
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
Skull Defect
Development of Three-dimensional Deep Learning for Automatic Design of Skull Implants
This project aims to develop an effective deep learning system to generate numerical implant geometry based on 3D defective skull models from CT scans.
- Trial name
- NCT05603949
- Testing
- 3D deep learning neural network system
- Where
- Taiwan
- Volunteers
- 6 people
- Sponsor
- Chang Gung Memorial Hospital