Clinical trials: Deep Learning
Glioma (Diagnosis), Liquid Biopsy
Combing a Deep Learning-Based Radiomics With Liquid Biopsy for Preoperative and Non-invasive Diagnosis of Glioma
This registry has the following objectives. First, according to the guidance of 2021 WHO of CNS classification, we constructed and externally tested a multi-task DL model for simultaneous diagnosis of tumor segmentation, glioma…
- Conditions
- Glioma (Diagnosis), Liquid Biopsy, Deep Learning
- Trial name
- NCT05536024
- Testing
- Prediction of glioma grading and molecular subtype
- Where
- 2 sites in China
- Volunteers
- 68 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
Nursing, Artificial Intelligence (AI)
AI-Assisted Smart Interactive Healthcare Robot
To address workforce shortages and increasing workloads in nursing, technological solutions and AI-powered robots for ward navigation have been introduced. However, limitations remain in their application to clinical care.
- Conditions
- Nursing, Artificial Intelligence (AI), Deep Learning, Mechine Learning
- Trial name
- NCT06972043
- Testing
- Intervention Group
- Where
- Taiwan
- Volunteers
- 160 people, healthy volunteers welcome
- Sponsor
- National Taiwan University Hospital
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.
Artificial Intelligence, Electrocardiogram
Artificial Intelligence-enabled ECG Detection of Congenital Heart Disease in Children: a Novel Diagnostic Tool
Congenital heart disease (CHD) is the most common congenital disease in children. The early detection, diagnosis and treatment of CHD in children is of great significance to improve the prognosis and reduce the mortality of…
- Conditions
- Artificial Intelligence, Electrocardiogram, Deep Learning, Congenital Heart Disease in Children
- Trial name
- AI-ECG-CHD (NCT06383546)
- Where
- China
- Volunteers
- healthy volunteers welcome
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Deep Learning, Head & Neck Squamous Cell Carcinoma
A Bidirectional Study of Individualized Postoperative Adjuvant Treatment Decision Model for Locally Advanced Head and Neck Squamous Cell Carcinoma Based on Multimodal Dynamic Data
Based on multimodal data, the investigators establish a dynamic deep learning model to conduct prognostic risk assessment for patients and recommend the 'most suitable' treatment/follow-up regimen after radical treatment…
- Trial name
- NCT07532928
- Where
- China
- Volunteers
- 571 people
- Sponsor
- Nanfang Hospital, Southern Medical University
Urolithiasis, Urinary Tract Stones
Detection of Urinary Stones on ULDCT With Deep-learning Image Reconstruction Algorithm
Urolithiasis has an increasing incidence and prevalence worldwide, and some patients may have multiple recurrences. Because these stone-related episodes may lead to multiple diagnostic examinations requiring ionizing radiation…
- Conditions
- Urolithiasis, Urinary Tract Stones, Renal Colic, Deep Learning Reconstruction
- Trial name
- URO DLIR (NCT04490343)
- Testing
- Abdominopelvic low dose CT
- Where
- France
- Volunteers
- 62 people
- Sponsor
- Centre Hospitalier Universitaire, Amiens
Bladder Cancer, Comorbidity
Impact of COMORBIDities After Radical Cystectomy Using a Predictive Method With Artificial Intelligence
Clinician and the multidisciplinary team meeting in oncologic urology (MMO) play a key-role in the decision making. An unexplained surgeon attributable variance, probably linked to the subjective "eyeball test" effect, was…
- Conditions
- Bladder Cancer, Comorbidity, Deep Learning
- Trial name
- COMORBID-AI (NCT05204186)
- Where
- France
- Volunteers
- 500 people
- Sponsor
- Centre Hospitalier Universitaire, Amiens
Breast Neoplasms, Artificial Intelligence (AI)
Non-Contrast Breast MRI Diagnosis and Risk Stratification Using DWI-Generated Synthetic Contrast Enhancement
This study is conducted under the ethics-approved project titled "Artificial Intelligence Solution for Simplifying the Diagnostic Workflow of Breast MRI''.The goal of this observational study is to develop an integrated breast…
- Conditions
- Breast Neoplasms, Artificial Intelligence (AI), Magnetic Resonance Imaging (MRI), Diffusion Magnetic Resonance Imaging
- Trial name
- NCT07598084
- Testing
- Non-contrast breast MRI diagnostic model
- Volunteers
- 12,000 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital
Endodontic Retreatment, Non-surgical Retreatment
Development and Validation of a Deep Learning Model to Predict Endodontic Retreatment Difficulty From Periapical Radiographs
The aim of this study is to develop and evaluate an artificial intelligence-based model capable of analyzing periapical radiographs of maxillary and mandibular molars to predict the difficulty level of non-surgical root canal…
- Conditions
- Endodontic Retreatment, Non-surgical Retreatment, Endodontics, AI (Artificial Intelligence)
- Trial name
- Ai Retreatment (NCT07611279)
- Testing
- Deep Learning Model to Predict Endodontic Retreatment Difficulty from Periapical Radiographs
- Volunteers
- 123 people
- Sponsor
- Cairo University
Colonoscopy, Colorectal Neoplasms
Interest of Artificial Intelligence in Cancer Screening Colonoscopy
Artificial Intelligence (AI) to predict the histology of polyps per colonoscopy, offers a promising solution to reduce variation in colonoscopy performance.
- Conditions
- Colonoscopy, Colorectal Neoplasms, Intestinal Polyps, Deep Learning
- Trial name
- IA COLO (NCT04921488)
- Testing
- screening colonoscopy
- Where
- 5 sites in France
- Volunteers
- 194 people
- Sponsor
- University Hospital, Bordeaux
Lung Cancer, Health Screening
Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT
The goal of this clinical trial is to evaluate whether an AI tool that alerts providers to patients at high 6-year risk of lung cancer based on their chest x-ray images will improve lung cancer screening CT participation.
- Conditions
- Lung Cancer, Health Screening, Early Cancer Detection, Deep Learning
- Trial name
- NCT06910956
- Testing
- CXR-LC
- Where
- United States
- Volunteers
- 1,500 people
- Sponsor
- Massachusetts General Hospital
Stroke Outcome Prediction Supported by Deep Learning Algorithm
STOP-stroke: STroke Outcome Prediction in the Acute Treatment Setting
The STOP-stroke project aims at improving prediction of outcome early after stroke. In order to achieve this, we need to understand reasons (important variables) for prediction in a real clinical prognostication process.
- Trial name
- STOP-STroke (NCT06534645)
- Where
- Switzerland
- Volunteers
- 250 people
- Sponsor
- University of Zurich
Contouring, Segmentation
Locally Optimised Contouring With AI Technology for Radiotherapy
LOCATOR is a multicentre phase II randomised clinical trial that is looking at the process of contouring in radiation treatment for breast cancer patients.
- Conditions
- Contouring, Segmentation, Radiation Therapy, Artificial Intelligence
- Trial name
- LOCATOR (NCT06546592)
- Testing
- AI assisted contouring
- Where
- 3 sites in Australia
- Volunteers
- 444 people, healthy volunteers welcome
- Sponsor
- Royal North Shore Hospital
Left Ventricular Ejection Fraction, Cardiac Magnetic Resonance Imaging
Evaluation of Left Ventricular Ejection Fraction Using an Accelerated Cardiac Cine-MRI Sequence With Deep Learning-based Image Reconstructions
Left ventricular hypertrophy (LVH) is a common condition that may result from hypertension, hypertrophic cardiomyopathy, aortic valve stenosis, or certain metabolic disorders.
- Conditions
- Left Ventricular Ejection Fraction, Cardiac Magnetic Resonance Imaging, Deep Learning, Image Reconstruction
- Trial name
- HVGLD (NCT07061821)
- Testing
- accelerated cardiac cine-MRI sequence
- Where
- France
- Volunteers
- 61 people
- Sponsor
- Centre Hospitalier Universitaire, Amiens
Magnetic Resonance Imaging, Cardiac Magnetic Resonance Imaging
Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions by Deep-Learning in Ischemic Heart Disease
Today, MRI is the gold standard for the precise assessment of left ventricular volume and function, but presents the drawback of having a long acquisition time and of generating motion artifacts, in particular respiratory…
- Conditions
- Magnetic Resonance Imaging, Cardiac Magnetic Resonance Imaging, Deep-Learning, Left Ventricular Ejection Fraction
- Trial name
- CINEDL (NCT05105984)
- Where
- France
- Volunteers
- 54 people
- Sponsor
- Centre Hospitalier Universitaire, Amiens
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
Carcinoma, Renal Cell, Diagnostic Imaging
Deep Learning for Automated Discrimination Between Stage T1-T2 and T3 Renal Cell Carcinoma on Contrast-Enhanced CT
This study aims to develop and validate a contrast-enhanced CT-based deep-learning model for automatic and accurate preoperative discrimination between T1-T2 and T3 renal cell carcinoma.
- Conditions
- Carcinoma, Renal Cell, Diagnostic Imaging, Pathology, Deep Learning
- Trial name
- NCT07166445
- Testing
- None intervention
- Where
- China
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Peking University First Hospital
Optic Neuropathy, Optic Neuropathy, Ischemic
Building Research With Artificial Intelligence in Neuro-Ophthalmology
The research team, recognized as a world leader in Artificial Intelligence for neuro-ophthalmology, has shown that it is possible to diagnose certain neuro-ophthalmologic or neurologic disorders from a single retinal fundus image…
- Conditions
- Optic Neuropathy, Optic Neuropathy, Ischemic, Optic Neuritis, Optic Nerve Diseases
- Trial name
- BRAIN (NCT06390579)
- Testing
- Deep learning algorithm applied on retrospectively collected color fundus photographs
- Where
- France
- Volunteers
- 693 people
- Sponsor
- Fondation Ophtalmologique Adolphe de Rothschild
ICL, Vault
Predictive Performance of a Generative Model for Corneal Tomography After ICL Implantation
To evaluate the efficacy of a corneal tomography Imaging model in predicting postoperative vault based on preoperative corneal topography in Implantable Collamer Lens (ICL) surgery.
- Conditions
- ICL, Vault, Deep Learning, AI (Artificial Intelligence)
- Trial name
- NCT07146737
- Testing
- Corneal tomography generation model after ICL surgery
- Where
- China
- Volunteers
- 818 people
- Sponsor
- Second Affiliated Hospital of Nanchang University
Deep Learning, Ultrasound
Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study
This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors.
- Conditions
- Deep Learning, Ultrasound, Bladder Cancer
- Trial name
- BCA-AI-US (NCT07111364)
- Testing
- observational diagnostic model development
- Where
- China
- Volunteers
- 400 people
- Sponsor
- Peking University First Hospital