Clinical trials: Deep Learning Model, open to volunteers
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
Gummy Smile
Deep Learning for Gummy Smile Segmentation
A gummy smile (excessive visibility of the gums when smiling) is not merely an aesthetic issue but also an important parameter in terms of periodontal health.
- Trial name
- NCT06965387
- Where
- Turkey (Türkiye)
- Volunteers
- 1,740 people, healthy volunteers welcome
- Sponsor
- Gazi University
Hemorrhage Stroke
Hemorrhage Stroke Decision Making Model Based Deep Learning (BrainHemoAI System)
Although hemorrhagic stroke also has the characteristics of high mortality and disability rates, and constitutes a major public health problem worldwide, there is a relative lack of in-depth research teams for hemorrhagic stroke…
- Trial name
- NCT07570680
- Testing
- Large language model
- Where
- China
- Volunteers
- 7,100 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
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
Cancer Diagnosis, Liver Cancer, Adult
Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening.
- Conditions
- Cancer Diagnosis, Liver Cancer, Adult, Cancer Screening, Colorectal Cancer (CRC)
- Trial name
- NCT06822413
- Testing
- No Interventions
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
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
Skin Lesions
Human-AI Uncertainty Callibration for Improved Skin Lesion Segmentation
The goal of this randomized controlled study is to compare the effect of a new, personalized uncertainty-aware decision model (FDM) to a standard image recognition model in improving the diagnostic accuracy while reducing…
- Trial name
- NCT07468357
- Testing
- Base Model, FDM
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- Copenhagen Academy for Medical Education and Simulation
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
Artificial Intelligence (AI), Deep Learning
The Construction and Effect Verification of a Deep Learning-based Automated Semantic Segmentation Model for Medical Imaging
Hepatocellular Carcinoma(HCC) is a common disease in China, ranking as the fourth most prevalent malignant tumor and the third leading cause of cancer-related deaths in the country.
- Conditions
- Artificial Intelligence (AI), Deep Learning, Laparoscopic Surgery
- Trial name
- NCT06864702
- Testing
- Whether the patient received diagnosis and treatment at Zhujiang Hospital of Southern Medical University and retained medical images such as abdominal
- Where
- China
- Volunteers
- 220 people, healthy volunteers welcome
- Sponsor
- Zhujiang Hospital
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
Heart Failure, Cardiomyopathies
Multimodal Physiologic State Intelligence Study
The OMNIPHYS study will investigate whether multimodal ultrasound and other routinely collected clinical and physiologic data can be combined with artificial intelligence to characterize changes in a person's physiologic state…
- Conditions
- Heart Failure, Cardiomyopathies, Pulmonary Hypertension, Myocarditis; Acute or Subacute
- Trial name
- OMNIPHYS (NCT07814118)
- Testing
- OMNIPHYS Multimodal Ultrasound Imaging System
- Where
- United States
- Volunteers
- 25,000 people, healthy volunteers welcome
- Sponsor
- Truway Health, Inc.
Kawasaki Disease, Chest X-ray for Clinical Evaluation
Clinical Study on an Artificial Intelligence-Assisted Chest Radiograph Model Based on Big Data and Deep Learning for Early Detection of Kawasaki Disease
The goal of this observational study is to develop an AI-based early warning system for Kawasaki Disease (KD) using chest X-rays (CXR) in children diagnosed with Kawasaki Disease. The main question[s] it aims to answer are: 1.
- Conditions
- Kawasaki Disease, Chest X-ray for Clinical Evaluation, Mucocutaneous Lymph Node Syndrome
- Trial name
- NCT07405658
- Testing
- AI-Based Early Warning System for Kawasaki Disease
- Where
- China
- Volunteers
- 20,000 people, healthy volunteers welcome
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
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
Peripheral Vein, Arterial Wave Reflections
Deep Learning Model for Predicting a Peripheral Venous Waveform-based Pulse Pressure Variation
Pulse pressure variation is a monitoring index that indicates the response to fluid therapy in patients receiving mechanical ventilation, and is used as a reference for patients with unstable hemodynamic conditions.
- Conditions
- Peripheral Vein, Arterial Wave Reflections, Pulse Pressure Variation, Stroke Volume Variation
- Trial name
- NCT06734650
- Testing
- peripheral waveform collection
- Where
- South Korea
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Seoul National University Bundang Hospital
Gingival Recessions
AI-Based Prediction of Root Coverage Outcome From Intraoral Photographs
This study evaluates whether the outcome of root coverage surgery can be predicted from a preoperative intraoral photograph. Adults with Cairo RT1,RT2 or RT3 gingival recessions treated with a coronally advanced flap and a…
- Trial name
- NCT07775365
- Testing
- Coronally advanced flap with subepithelial connective tissue graft, Deep learning based prediction of root coverage outcome
- Where
- Turkey (Türkiye)
- Volunteers
- 36 people, healthy volunteers welcome
- Sponsor
- Marmara University
Ophthalmic Imaging, Deep Learning
Diagnostic Performance of an AI-based Model for TCM Constitution Classification Using Ophthalmic Imaging
To evaluate the diagnostic performance of a multimodal deep learning model for identifying biased Traditional Chinese Medicine (TCM) constitutions using ophthalmic imaging
- Conditions
- Ophthalmic Imaging, Deep Learning, Artificial Intelligence (AI), Traditional Chinese Medicine Constitution
- Trial name
- NCT07127939
- Testing
- AI-based Ocular Diagnosis Model for TCM Constitutions
- Where
- China
- Volunteers
- 1,024 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
Dementia (Diagnosis), Alzheimer Dementia (AD)
Speech-Based Artificial Intelligence for Detection of Dementia in Danish Patients (DetectAI)
The goal of this observational study is to learn if an artificial intelligence (AI)-based speech analysis tool can identify which patients with memory problems need specialist evaluation at a memory clinic.
- Conditions
- Dementia (Diagnosis), Alzheimer Dementia (AD), Vascular Dementia (VaD), Lewy Body Dementia (LBD)
- Trial name
- DetectAI (NCT07200739)
- Testing
- Mini-mental State Examination, Addenbrooke's Cognitive Examination, Speech Task - Picture Description
- Where
- Denmark
- Volunteers
- 440 people, healthy volunteers welcome
- Sponsor
- Zealand University Hospital
Breast Cancer
AI Model for Classifying Breast Cancer From Histopathology Images
Breast cancer, a prevalent and potentially fatal disease, underscores the need for early and accurate detection to improve patient outcomes.
- Trial name
- NCT06717984
- Testing
- Biopsy, Mastectomy, Histopathology
- Where
- Bangladesh
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- Taufiq Hasan, PhD
Bone Aging, Osteoporosis Diagnosis
Automated Bone Age Estimation From Noncontrast Abdominal CT Using Deep Learning
This study is a retrospective analysis that uses abdominal CT scans, which were originally taken for other medical reasons, to estimate bone age.
- Trial name
- NCT07162168
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital