Clinical trials: Deep Learning Model, open to volunteers
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
Deep Vein Thrombosis
Systematic Machine Learning Algorithm for Rapid Thrombosis Detection
The goal of this clinical trial is to compare the use of a machine learning-based algorithm and point-of-care D-dimer to laboratory D-dimer and compression ultrasound to exclude deep vein thrombosis in the under extremities in…
- Trial name
- DVT-SMART (NCT06842446)
- Testing
- POC D-dimer, POC ultrasound, Machine learning model
- Where
- Norway
- Volunteers
- 1,000 people
- Sponsor
- Ostfold Hospital Trust
Cardiac Amyloidosis, Transthyretin Amyloidosis
Retrospective Identification of Scintigraphic Cardiac Amyloidosis (RISCA)
This study aims to determine the positive predictive value of incidental cardiac uptake on bone scintigraphy for diagnosing transthyretin cardiac amyloidosis, in patients who underwent scintigraphy for reasons other than…
- Trial name
- RISCA (NCT06921408)
- Volunteers
- 57 people
- Sponsor
- University Hospital, Lille
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
Renal Tumors
Federated Learning in Renal Tumor Model
This is a multicenter, retrospective and prospective diagnostic clinical trial evaluating the effectiveness and safety of CascadeDiagnose Renal Tumor CT, an AI-assisted detection system for renal tumors based on contrast-enhanced…
- Trial name
- NCT07841756
- Where
- 6 sites in China
- Volunteers
- 3,000 people
- Sponsor
- First Affiliated Hospital of Guangxi Medical University
Glaucoma
Glaucoma Screening Using Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program
Glaucoma is major cause of irreversible blindness and is characterized by optic nerve damage and visual field loss. Screening for glaucoma is challenging due to lack of a simple, accurate, cost-efficient and standardized process.
- Trial name
- AIGS (NCT07243665)
- Testing
- Artificial Intelligence model to detect glaucoma, No intervention
- Where
- Singapore
- Volunteers
- 1,040 people
- Sponsor
- Singapore Eye Research Institute
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
Type II Endoleak, Abdominal Aortic Aneurysm Enlargement
Deep-learning Predictors of Abdominal Aortic Aneurysm Enlargement in Type II Endoleaks After Endovascular Aortic Repair: The RADAR Study
Background and rationale: Abdominal aortic aneurysm (AAA) is a weakening and enlargement of the main artery in the abdomen. Endovascular aneurysm repair (EVAR) is a minimally invasive treatment used to repair an AAA.
- Trial name
- RADAR (NCT07783126)
- Testing
- Artificial intelligence model analyzing preoperative CT angiography
- Volunteers
- 1,250 people
- Sponsor
- Ente Ospedaliero Cantonale, Bellinzona
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
Esophageal Squamous Cell Carcinoma, Neoadjuvant Immunochemotherapy
Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy
This study aims to develop and validate a deep learning model to predict pathological complete response (pCR) in patients with esophageal squamous cell carcinoma who have undergone neoadjuvant immunochemotherapy.
- Conditions
- Esophageal Squamous Cell Carcinoma, Neoadjuvant Immunochemotherapy, Pathological Complete Response, Deep Learning
- Trial name
- DL-ESCC (NCT07088354)
- Testing
- The high-throughput extraction of large amounts of quantitative image features from medical images
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Tongji Hospital
Pulmonary Nodules, Lung Neoplasms
Deep Learning Time-Series Prediction of Long-Term Growth Patterns of Pulmonary Ground-Glass Nodules Using Serial CT
Pulmonary ground-glass nodules (GGNs) are commonly found on chest CT scans. Some stay stable for years, while others slowly or rapidly turn into lung cancer.
- Conditions
- Pulmonary Nodules, Lung Neoplasms, Adenocarcinoma of Lung
- Trial name
- GGN-Trajectory (NCT07647692)
- Testing
- Serial Thin-Slice Chest CT
- Where
- China
- Volunteers
- 4,750 people
- Sponsor
- Peking University People's Hospital
Bladder Cancer
Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
Muscle invasive bladder cancer (MIBC) has a poor prognosis even after radical cystectomy. Postoperative survival stratification based on radiomics and deep learning may be useful for treatment decisions to improve prognosis.
- Trial name
- NCT06092450
- Testing
- develop and validate a deep learning radiomics model based on preoperative enhanced CT image
- Where
- China
- Volunteers
- 500 people
- Sponsor
- First Affiliated Hospital of Chongqing Medical University
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
ST Elevation (STEMI) Myocardial Infarction
Development and Validation of a Cardiac Magnetic Resonance-Based Multimodal Deep Learning Model for Long-Term Outcome Prediction in ST-Segment Elevation Myocardial Infarction
Objective: This study aims to develop and test a novel artificial intelligence-based prediction model. This model will integrate cardiac magnetic resonance imaging and clinical data to predict the long-term risk of major adverse…
- Trial name
- NCT07277400
- Where
- China
- Volunteers
- 800 people
- Sponsor
- Qian geng
Acute Ischemic Stroke
Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA)
Stroke is the leading cause of disability-adjusted life years (DALYs) in China, imposing a heavy burden on society and families.
- Trial name
- AURORA (NCT06009315)
- Where
- China
- Volunteers
- 949 people
- Sponsor
- Beijing Tiantan Hospital
Obstructive Sleep Apnea (OSA), Polysomnography
Multimodal Deep Learning Model for Predicting the Apnea-Hypopnea Index in Obstructive Sleep
This study aims to develop a multimodal deep learning model that integrates noninvasive signals to predict the severity of obstructive sleep apnea.
- Trial name
- NCT07447999
- Testing
- electronic stethoscope, fingertip pulse oximeter, pressure-sensing mattresses
- Where
- Taiwan
- Volunteers
- 150 people
- Sponsor
- Fu Jen Catholic University
Hepatecellular Carcinoma, Hepatectomy
AI-Based Prediction of HCC Recurrence Patterns After Resection (APAR)
This observational study aims to validate a deep learning model for predicting aggressive recurrence patterns in patients with early-stage liver cancer (HCC) after surgery.
- Trial name
- NCT07062380
- Testing
- Curative liver resection, Real-world multimodal therapy
- Where
- China
- Volunteers
- 353 people
- Sponsor
- Tongji Hospital
Gastrectomy for Gastric Cancer, Gastric Cancer
AI-assisted Decision-making of Reoperation for Postoperative Bleeding of Gastric Cancer
The goal of this observational study is to develop and validate a deep learning model to dynamically assess postoperative bleeding risk and assist in decision-making for re-operation in adult patients (≥18 years) diagnosed with…
- Trial name
- NCT07525765
- Where
- China
- Volunteers
- 7,000 people
- Sponsor
- First Affiliated Hospital of Zhejiang University