Clinical trials: Artificial Intelligence (AI) in Diagnosis, active
Ventricular Dysfunction, Left, Ventricular Function, Left
Federated Learning for Point-of-Care Cardiac Ultrasound
This prospective, multicenter study will evaluate a federated machine-learning system designed to analyze focused cardiac point-of-care ultrasound examinations.
- Conditions
- Ventricular Dysfunction, Left, Ventricular Function, Left, Echocardiography, Ultrasonography
- Trial name
- FL-POCUS (NCT07800962)
- Testing
- Focused Cardiac Point-of-Care Ultrasonography, FL-POCUS Federated Machine-Learning Analysis System
- Where
- United States
- Volunteers
- 3,000 people
- Sponsor
- Truway Health, Inc.
Mycosis Fungoides of Skin (Diagnosis), Artificial Intelligence (AI) in Diagnosis
AI in MF Diagnosis
The aim of this observational study is to evaluate the diagnostic performance of an AI algorithm in the histopathological diagnosis of MF compared to certified dermatopathologists.
- Trial name
- AI\MF (NCT07795242)
- Testing
- this study does not include any intervention
- Where
- Egypt
- Volunteers
- 50 people
- Sponsor
- Al-Azhar University
Emergency Medicine, AI (Artificial Intelligence)
AI-support in Emergency Medicine
The purpose of this study is to investigate whether the use of generative artificial intelligence (AI) as a support tool can improve physicians' ability to establish accurate differential diagnoses in emergency care.
- Conditions
- Emergency Medicine, AI (Artificial Intelligence), Differential Diagnosis
- Trial name
- NCT07766863
- Where
- Sweden
- Volunteers
- 500 people
- Sponsor
- Region Stockholm
Hepatic Disease, Biliary Disease
Development and Prospective Validation of an AI-Based Diagnostic Model for Hepato-Pancreato-Biliary Diseases
The rapid advancement of artificial intelligence (AI) has expanded its applications in healthcare, particularly in diagnostic assistance, intelligent triage, and patient interaction.
- Conditions
- Hepatic Disease, Biliary Disease, Pancreas Disease, Artificial Intelligence (AI) in Diagnosis
- Trial name
- NCT07716670
- Testing
- AI Integration type 1, AI Integration type 2
- Volunteers
- 400 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Preterm Birth, Artificial Intelligence (AI) in Diagnosis
Does AI Make Clinicians More Appropriately Confident? A Randomized Study in Preterm Birth Prediction
The goal of this randomized questionnaire-based study is to evaluate how different presentations of artificial intelligence (AI) decision support influence clinical judgment among medical doctors working in obstetrics and…
- Trial name
- NCT07402668
- Testing
- AI prediction (binary), AI risk estimate (%)
- Where
- 18 sites in Denmark
- Volunteers
- 125 people, healthy volunteers welcome
- Sponsor
- Copenhagen University Hospital, Rigshospitalet
Cephalometric Analysis, Cephalometry
Comparison of Digital Analysis and Artificial Intelligence for Cephalometric Tracing
This study aims to evaluate the accuracy and reliability of artificial intelligence (AI)-based cephalometric analysis compared with digital manual tracing.
- Conditions
- Cephalometric Analysis, Cephalometry, Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis
- Trial name
- NCT07664488
- Testing
- Cephalometric Analysis
- Where
- Italy
- Volunteers
- 100 people
- Sponsor
- University of Pavia
Emergency Medicine, Artificial Intelligence (AI)
Diagnostic Accuracy of GPT-4o and Claude for HEART Score Calculation in Chest Pain
This prospective observational diagnostic accuracy study evaluates whether large language models (LLMs) - GPT-4o (OpenAI, gpt-4o-2024-11-20) and Claude (Anthropic, claude-sonnet-4-6) - can accurately calculate HEART scores from…
- Conditions
- Emergency Medicine, Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis, Chest Pain Rule Out Myocardial Infarction
- Trial name
- LLM-HEART (NCT07626060)
- Testing
- GPT-4o HEART Score Calculator, Claude HEART Score Calculator, Three-Expert Consensus HEART Score
- Where
- Turkey (Türkiye)
- Volunteers
- 690 people
- Sponsor
- Marmara University Pendik Training and Research Hospital
Lung Neoplasms, Bronchoscopy
Feasibility and Preliminary Performance of an AI Prototype for Digital ROSE During EBUS-TBNA and Peripheral TBNA: a Prospective Pilot Study (AI-ROSE-FEAS)
Rapid On-Site Evaluation (ROSE) of cytological slides obtained during EBUS-TBNA improves diagnostic yield by providing real-time adequacy assessment and preliminary diagnostic orientation after each needle pass.
- Conditions
- Lung Neoplasms, Bronchoscopy, AI (Artificial Intelligence), Mediastinal ( Chest) Masses
- Trial name
- AI-ROSE-FEAS (NCT07662967)
- Testing
- ROSE
- Volunteers
- 65 people
- Sponsor
- Azienda Ospedaliera di Rilievo Nazionale A.Cardarelli
Thoracic Diseases, Chest CT Scan
AI-Assisted Chest-CT Reporting for Enhanced Speed and Quality (The DOUBLE-ACE Study)
The goal of this observational study is to learn if an AI assistant tool can help doctors who read chest CT scans (called radiologists) write their reports faster and just as well or better.
- Conditions
- Thoracic Diseases, Chest CT Scan, Artificial Intelligence (AI) in Diagnosis
- Trial name
- DOUBLE-ACE (NCT07640906)
- Testing
- An AI-assisted reporting system integrated into the clinical workflow, providing automated draft generation to assist with chest CT interpretation
- Where
- 2 sites in China
- Volunteers
- 75 people
- Sponsor
- Shanghai Zhongshan Hospital
Preterm Birth, Artificial Intelligence (AI) in Diagnosis
The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice
This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different…
- Trial name
- NCT07598097
- Testing
- Cervical ultrasound image acquisition
- Where
- Denmark
- Volunteers
- 2,000 people
- Sponsor
- Copenhagen University Hospital, Rigshospitalet
Breast Cancer Screening, Artificial Intelligence (AI)
Screening Mammography: Single Reading by One Radiologist With AI vs. Double Reading by Two Radiologists (AI-BCSQ)
A randomized prospective study comparing the evaluation of mammography images in a breast cancer screening programme by a single radiologist with AI support versus standard double reading by two radiologists without AI support.
- Conditions
- Breast Cancer Screening, Artificial Intelligence (AI), Breast Cancer Screening and Diagnosis
- Trial name
- AI-BCSQ (NCT07075679)
- Testing
- Group with AI iCAD version 3, Group without AI
- Where
- Czechia
- Volunteers
- 8,000 people, healthy volunteers welcome
- Sponsor
- University Hospital Olomouc
Diabetic Foot Ulcer (DFU), Diabete Mellitus
AI-Based Diabetic Foot Recurrence Cohort
Diabetic foot ulcer (DFU) is a major adverse outcome of diabetes, which itself is one of the most significant chronic diseases. The recurrence of DFU involves multiple risk factors, including altered foot loading patterns…
- Conditions
- Diabetic Foot Ulcer (DFU), Diabete Mellitus, Diabetic Foot Ulcer Treatment, Artificial Intelligence (AI) in Diagnosis
- Trial name
- NCT07452354
- Testing
- Researchers predefined groups based on risk stratification to formulate personalized follow-up strategies.
- Where
- China
- Volunteers
- 200 people
- Sponsor
- Peking University Third Hospital
Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
This study aims to validate the use of an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated PAP.
- Conditions
- Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis, Hypertension, Pulmonary
- Trial name
- ADDPH (NCT07079592)
- Testing
- AI-ECG Guidance
- Where
- Taiwan
- Volunteers
- 8,666 people
- Sponsor
- National Defense Medical Center, Taiwan
Diagnosis, Clinical Decision-making
Reasoning Enrichment With Feedback From IA in NEphrology Trial
The goal of this clinical trial is to learn how artificial intelligence (AI) may help doctors make diagnoses in kidney medicine.
- Conditions
- Diagnosis, Clinical Decision-making, Artificial Intelligence (AI) in Diagnosis, Decision Support Systems, Clinical
- Trial name
- REFINe (NCT07352475)
- Testing
- AI suggestion
- Where
- France
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- University Hospital, Lille
Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis
A Multi-center Study on Artificial Intelligence-Based Quantitative Evaluation of Echocardiography
This project aims to collaborate with multiple medical institutions to verify the accuracy, stability, and clinical application value of AI algorithms in echocardiographic quantitative measurement through multi-center clinical…
- Conditions
- Artificial Intelligence (AI), Artificial Intelligence (AI) in Diagnosis, Cardiovascular Diseases (CVD), Echocardiography
- Trial name
- MAIQUEE (NCT07133516)
- Where
- 37 sites in China
- Volunteers
- 1,600 people, healthy volunteers welcome
- Sponsor
- First Hospital of China Medical University
Artificial Intelligence (AI) in Diagnosis
Human-AI Collaborative INSIGHT Diagnostic Workflow for in Breast Cancer With Extensive Intraductal Component
The goal of this clinical trial is to see if an artificial intelligence (AI)-assisted method helps doctors more accurately detect invasive breast cancer in people with a specific type of tumor called "extensive intraductal…
- Trial name
- INSIGHT-EIC (NCT07060599)
- Testing
- INvasion Screening with Intelligent Guidance for Histopathology Triage (INSIGHT) Workflow
- Where
- China
- Volunteers
- 480 people
- Sponsor
- Sun Yat-sen University
Artificial Intelligence (AI) in Diagnosis, Artificial Intelligence Supported Image Reviewing
The Impact of Artificial Intelligence on Dentists' Decision-Making Process During Caries Detection
This study aims to evaluate the influence of artificial intelligence (AI) on the decision-making process for intervention after caries lesion detection.
- Trial name
- DECIDE-AI (NCT07027189)
- Testing
- Artificial intelligence in diagnosis
- Where
- Netherlands
- Volunteers
- 25 people, healthy volunteers welcome
- Sponsor
- Radboud University Medical Center
Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis
AI-Based Prediction of Lymph Node Metastasis in Gastric Cancer Using Preoperative Multimodal Data
This study aims to develop and validate an artificial intelligence (AI) system that can predict whether lymph node metastasis has occurred in patients with gastric cancer before surgery.
- Conditions
- Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis, Artificial Intelligence (AI) in Diagnosis
- Trial name
- NCT06957678
- Testing
- Artificial Intelligence-Based Predictive Model for Lymph Node Metastasis
- Where
- China
- Volunteers
- 1,200 people
- Sponsor
- Qun Zhao