Clinical trials: Deep Learning
Hemoglobin Level Measurement, Hemoglobin Level Estimation
Non-Invasive Estimation of Hemoglobin Levels in Blood Using Combined Deep Learning Methods
Hemoglobin is an important protein that gives the blood its red color and helps transport oxygen to organs. There are quite a lot of people in the world who need to have their hemoglobin levels checked regularly, especially…
- Trial name
- NCT04865224
- Testing
- hemoglobin estimation
- Where
- Turkey (Türkiye)
- Volunteers
- 353 people, healthy volunteers welcome
- Sponsor
- Karabuk University
Class I Malocclusion, Class II Div 1 Malocclusion
Assesment of Ethnic Bias in an Artificial Intelligence Based Orthodontic Diagnosis System
This study explores how artificial intelligence (AI) can be used in orthodontics, which is the area of dentistry that focuses on correcting jaw and bite problems.
- Conditions
- Class I Malocclusion, Class II Div 1 Malocclusion, Class II Division 2 Malocclusion, Class III Malocclusion
- Trial name
- NCT07162753
- Where
- Turkey (Türkiye)
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- Bezmialem Vakif University
Scoliosis Patients
Artificial Intelligence and Scoliosis
The aim of the study to use artificial intelligence technology in assessment of scoliosis degree of severity and to personalize for treatment plan for each pa tient .
- Trial name
- NCT06589583
- Where
- Egypt
- Volunteers
- 5,000 people, healthy volunteers welcome
- Sponsor
- Delta University for Science and Technology
Labrum Injury of the Hip Joint
Research on Acetabular Labrum Injury Based on MR: Multi-angle Deep Learning Model
The purpose of this study is to study the MRI images of acetabular labrum injury by deep learning method, and try to establish a combination model of axial and coronal serial images, and compare with the diagnostic accuracy of…
- Trial name
- NCT04950036
- Testing
- Diagnostic Test
- Where
- China
- Volunteers
- 1,261 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Breast Cancer
Artificial Intelligence in Mammography-Based Breast Cancer Screening
Breast cancer (BC) is the most common cancer among women in worldwide and the second leading cause of cancer-related death. As the corner stone of BC screening, mammography is recognized as one of useful imaging modalities to…
- Trial name
- NCT04156880
- Testing
- mammography
- Where
- Hong Kong
- Volunteers
- healthy volunteers welcome
- Sponsor
- Chinese University of Hong Kong
Artificial Intelligence, Submerging Tooth
A Deep Learning Approach to Submerged Teeth Classification and Detection
Objectives: The study aimed to compare the success and reliability of an artificial intelligence application in the detection and classification of submerged teeth in orthopantomography (OPG).
- Trial name
- NCT04309851
- Testing
- deep learning
- Where
- Turkey (Türkiye)
- Volunteers
- 74 people, healthy volunteers welcome
- Sponsor
- Eskisehir Osmangazi University
Breast Cancer
Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization
The correct categorization of breast density is essential to adapt the diagnostic examination to the needs of each patient. Assessment of breast density is performed visually by radiologists.
- Trial name
- NCT05021055
- Volunteers
- 277 people, healthy volunteers welcome
- Sponsor
- Hospital Italiano de Buenos Aires
PechaKucha Presentation, Traditional PowerPoint Presentation
Effect of PechaKucha (PK)Presentation Method on Nursing Students' Satisfaction Level With Deep Breathing and Cough Exercise Skills and Education Method
ABSTRACT Aim: The aim of this study is to examine the effect of the PK presentation method on nursing students' deep breathing and cough exercise skills and the students' level of satisfaction with this method.
- Trial name
- NCT06862024
- Testing
- Deep Breathing and Cough Exercise Skills, Satisfaction with the training method
- Where
- Turkey (Türkiye)
- Volunteers
- 96 people, healthy volunteers welcome
- Sponsor
- Eastern Mediterranean University
Parkinson Disease, Alzheimer Disease
Application of AI Technology for the Diagnosis and Treatment of Geriatric Diseases
1) Characteristics of handwriting, gait, speech, eye movements, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers in patients with Alzheimer's disease.
- Conditions
- Parkinson Disease, Alzheimer Disease, Nervous System Diseases, Geriatric Diseases
- Trial name
- NCT06295263
- Testing
- Handwriting, gait, speech, eye movements, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers
- Where
- China
- Volunteers
- 460 people, healthy volunteers welcome
- Sponsor
- Qilu Hospital of Shandong University
Root Canal
AI-Based Root Canal Length, Curvature, and Morphology Assessment Using CBCT
The primary aim of this study is to develop, evaluate, and validate a deep learning-based software system capable of generating automated, comprehensive clinical reports that detect, segment, and quantify root canal curvature…
- Trial name
- NCT07843992
- Testing
- AI-Based Deep Learning System for Root Canal Assessment
- Volunteers
- 155 people, healthy volunteers welcome
- Sponsor
- Cairo University
Moyamoya Disease, Intracranial Hemorrhages
5T MRI and Metabolomics-Based Hemorrhage Risk Prediction in Moyamoya Disease
Intracranial hemorrhage is a leading cause of death and disability in patients with moyamoya disease (MMD), yet clinically available tools for predicting long-term hemorrhage risk are lacking.
- Conditions
- Moyamoya Disease, Intracranial Hemorrhages, Stroke
- Trial name
- NCT07781579
- Where
- China
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- Beijing Hospital
Lymph Nodes With Tumor Metastasis
Predicting Tumor Origin Based on Deep Learning of Lymph Node Puncture Cytology
In this study, the investigators aimed to construct a deep learning diagnostic model that uses cytological images to predict primary unknown tumor origins in patients with tumors combined with lymph node metastases.
- Trial name
- NCT06810349
- Where
- China
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- West China Hospital
Otitis Media Acute
Clinical Development of Deep Learning for the OtoSight
The objective of this study is to clinically develop and evaluate a machine learning approach to improve the performance and data interpretation of the PhotoniCare OtoSight Middle Ear Scope in pediatric patients presenting at the…
- Trial name
- NCT04722770
- Testing
- PhotoniCare OtoSight Middle Ear Scope
- Where
- United States
- Volunteers
- 188 people, healthy volunteers welcome
- Sponsor
- PhotoniCare, Inc.
Eyelid Diseases
Assessment of Eyelid Topology and Kinetics Based on Deep Learning Method
This study plans to assess eyelid topology (such as margin reflex distance, eyelid contour, and corneal exposure area) and blinking (such as frequency, velocity, and duration), using deep learning method to automatically extract…
- Trial name
- NCT04921020
- Testing
- Photography
- Where
- China
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Endocrine Diseases
Performance of the Diagnostic Value of Bone Age Assessment Software Based on Deep Learning in Chinese Children
High accuracy and precision bone age assessment is very important for the diagnosis and treatment monitoring of various pediatric diseases.
- Trial name
- NCT05137301
- Testing
- X-ray bone age instrument
- Where
- China
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Tongji Hospital
Tumor
Clinical Application Value of Deep Learning-Based "Opportunistic Screening" for Malignant Tumors on Routine Non-Contrast Chest-Abdomen-Pelvis CT
This study aims to develop and validate a deep learning-based opportunistic multi-cancer screening system using routine non-contrast chest-abdomen-pelvis CT examinations, including CHANCE-Breast, CHANCE-Liver, CHANCE-Kidney, and…
- Trial name
- NCT07639567
- Where
- China
- Volunteers
- 100,000 people, healthy volunteers welcome
- Sponsor
- Lian Yang
BIS, BIS-EEG
Deep Learning Framework for Continuous Depth of Anesthesia Forecasting
The integration of Artificial Intelligence (AI) in anesthesiology offers the potential to shift patient monitoring from reactive to predictive.
- Conditions
- BIS, BIS-EEG, Artifical Intelligence, Intraoperative
- Trial name
- NCT07536230
- Where
- Belgium
- Volunteers
- 115 people, healthy volunteers welcome
- Sponsor
- Universitair Ziekenhuis Brussel
Lateral Ligament, Ankle
Deep Learning of Anterior Talofibular Ligament: Comparison of Different Models
The purpose of this study is to study the injury of the anterior talofibular ligament by deep learning method and compare a variety of different deep learning models to establish a deep learning method that can accurately…
- Trial name
- NCT04955067
- Testing
- Diagnositic test
- Where
- China
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Childhood Obesity
Latinx Family Wellness
Childhood is an opportune time to intervene in obesity because behaviors that are developed during this time can have long-lasting effects and disrupt trajectories of obesity.
- Trial name
- NCT05735600
- Testing
- AyuDa Virtual: Aprender y Utilizar Decisiones Apreciables (Spanish) - Learning and Utilizing Significant Choices (English), AyuDa Written: Aprender y Utilizar Decisiones Apreciables (Spanish) - Learning and Utilizing Significant Choices (English)
- Where
- 2 sites in United States
- Volunteers
- 57 people, healthy volunteers welcome
- Sponsor
- Ana Maria Linares
Ophthalmology, Artificial Intelligence
Screening and Identifying Hepatobiliary Diseases Via Deep Learning Using Ocular Images
Artificial Intelligence may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in individuals with hepatobiliary disorders.
- Conditions
- Ophthalmology, Artificial Intelligence, Hepatobiliary Disease
- Trial name
- NCT04213183
- Testing
- Hepatobiliary Disorders
- Where
- China
- Volunteers
- 1,789 people, healthy volunteers welcome
- Sponsor
- Sun Yat-sen University