Clinical trials: Deep Learning
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
Deep Learning
Deep Learning Reconstruction Algorithms in Dual Low-dose CTA
The goal of this observational study is to evaluate the impact of deep learning image reconstruction on the image quality and diagnostic performance of double low-dose CTA.
- Trial name
- NCT06372756
- Testing
- Deep learning image reconstruction
- Where
- China
- Volunteers
- 1,200 people, healthy volunteers welcome
- Sponsor
- Hao Tang
Ovarian Cancer
Ovarian Cancer Identification on CT Using Deep Learning
Ovarian cancer remains the deadliest gynecologic malignancy, with poor survival rates largely due to late-stage diagnosis. Early detection is crucial, yet no universally accepted screening method exists.
- Trial name
- NCT06851429
- Where
- 2 sites in Taiwan
- Volunteers
- 12,578 people, healthy volunteers welcome
- Sponsor
- Chang Gung Memorial Hospital
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
Anterior Segment Diseases
Multimodal Deep Learning Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases
Accurate and comprehensive interpretation of anterior segment diseases from slit-lamp and smartphone photographs remains a clinical challenge due to the limited specificity and structure of existing Artificial Intelligence tools.
- Trial name
- NCT07447973
- Testing
- Multimodal Vision-language Model Diagnosis
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- Guangdong Provincial People's Hospital
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
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
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
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
Esophageal Squamous Cell Carcinoma
Changhai Multimodal Esophageal Cancer Cohort
The burden of esophageal squamous cell carcinoma (ESCC) in China is substantial, with 85% of the cancers being in the progressive stage.
- Trial name
- CMECC (NCT06410677)
- Testing
- DNA Sequencing, RNA Sequencing
- Where
- China
- Volunteers
- 110 people, healthy volunteers welcome
- Sponsor
- Wangluowei
Echocardiography
Developing Echocardiography Image Quality Management System Based on Deep Learning
To develop an echocardiography image quality management system based on deep learning to achieve objective and accurate automatic echocardiography image quality control.
- Trial name
- NCT05633732
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Extra Canals
AI Detection Model of Extra Root Canals in Mandibular Premolars Using CBCT Scans
Successful endodontic treatment depends on the complete identification and management of the entire root canal system. Missed root canals are a major cause of endodontic failure, particularly in mandibular premolars, which…
- Trial name
- NCT07689708
- Testing
- AI Model to detect any extra canals in mandibular premolars
- Volunteers
- 272 people, healthy volunteers welcome
- Sponsor
- Cairo University
Alzheimer Disease, Mild Cognitive Impairment
Multimodal Deep Learning for the Diagnosis and Assessment of Alzheimer's Disease
Alzheimer's disease (AD) is the most common dementia and has been one of the most expensive diseases with the highest lethality.
- Trial name
- NCT06081569
- Testing
- gait video; speech video; facial expression video;
- Volunteers
- 300 people, healthy volunteers welcome
- Sponsor
- First Hospital of China Medical University
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
Prostate Cancer
Evaluation of Rapid T2-weighted and DWI MR Sequences Reconstructed by Deep Learning for Prostate Imaging
MR prostate exam is essential for the diagnosis, workup and follow-up of prostate cancer. It allows to detect subclinical prostate cancer following an increase in the level of PSA.
- Trial name
- DLRPRO (NCT06094322)
- Testing
- MR prostate exam
- Where
- France
- Volunteers
- 34 people, healthy volunteers welcome
- Sponsor
- Centre Hospitalier Universitaire, Amiens
Osteoporosis
AI Model for Bone Mineral Density Prediction From X-Ray Images
Osteoporosis, a pervasive skeletal disorder characterized by diminished bone strength predisposing individuals to an increased risk of fractures, presents a substantial public health challenge globally.
- Trial name
- NCT06652061
- Testing
- Dual Energy X-Ray Absorptiometry Scan (DEXA Scan), X-Ray (Hip and Spine)
- Where
- Bangladesh
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Bangladesh University of Engineering and Technology
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
Congenital Heart Disease
Interpretation of Fetal Echocardiography by Artificial Intelligence
The study to be performed aims to design and develope an automated Intelligent Decision Support System for fetal echocardiography that can significantly assist the obstetric physician in the improvement of detection of fetal…
- Trial name
- LIFE (NCT05090306)
- Testing
- Routine ultrasound examination
- Where
- Romania
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- University of Medicine and Pharmacy Craiova
Intracranial Aneurysm, CT Angiography
IDEAL Study: Blinded RCT for the Impact of AI Model for Cerebral Aneurysms Detection on Patients' Diagnosis and Outcomes
This study (IEDAL study) intends to prospectively enroll more than 6450 patients who will undergo head CT angiography (CTA) scanning in the outpatient clinic.
- Conditions
- Intracranial Aneurysm, CT Angiography, Deep Learning, Double Bind Interaction
- Trial name
- IDEAL (NCT06118840)
- Testing
- True-AI-integrated intracranial aneurysms diagnosis strategy
- Where
- 21 sites in China
- Volunteers
- 6,450 people, healthy volunteers welcome
- Sponsor
- Jinling Hospital, China