Clinical trials: Deep Learning Model
Hepatocellular Carcinoma, Contrast-enhanced Ultrasound
Clinical Decision Biological Biomarker and Prognosis Prediction of Hepatocellular Carcinoma by Deep Learning
Developing a deep learning model based on contrast-enhanced ultrasound (CEUS) to predict the prognosis of hepatocellular carcinoma (HCC) and aid choose operation decisions
- Conditions
- Hepatocellular Carcinoma, Contrast-enhanced Ultrasound, Prognosis, Surgery
- Trial name
- NCT05257694
- Testing
- Surgery, Ablation (Microwave ablation or Radiofrequency ablation)
- Where
- China
- Volunteers
- 1 people
- Sponsor
- Ping Liang
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
Myopia, Small-incision Lenticule Extraction (SMILE) Surgery
Potential Risk Factors and Predictive Model Construction of OBL During SMILE
To explore the prediction of OBL by deep learning model in SMILE surgery
- Trial name
- NCT06577012
- Testing
- Small incision lenticule extraction
- Where
- China
- Volunteers
- 4,678 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital of Nanchang University
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.
Acute Appendicitis
IA Model for Acute Appendicitis in CT
the investigators's study group has developed a fully automated 3D convolutional neural network (CNN)-based diagnostic framework using information of appendix (IA) model to identify non-appendicitis and simple and complicated…
- Trial name
- NCT06175169
- Testing
- Information of Appendix (IA) model
- Where
- South Korea
- Volunteers
- 568 people
- Sponsor
- Hallym University Medical Center
Pancreatic Neoplasms
A Deep Learning Radiomics Model for Predicting Occult Peritoneal Metastases of Pancreatic Adenocarcinoma
Occult peritoneal metastases (OPM) in patients with pancreatic ductal adenocarcinoma (PDAC) are frequently overlooked during imaging.
- Trial name
- NCT06336694
- Testing
- surgery or diagnostic staging laparoscopy
- Where
- China
- Volunteers
- 302 people
- Sponsor
- First Affiliated Hospital, Sun Yat-Sen University
Pediatric Obstructive Sleep Apnea, Polysomnography
Development of a Multimodal Deep Learning Model for Pediatric Patients
This study aims to develop a multimodal data-driven model integrating multiple noninvasive physiological signals to assess the severity of pediatric sleep-disordered breathing, using standard clinical sleep study results as the…
- Trial name
- NCT07805486
- Testing
- fingertip pulse oximeter, pressure-sensing mattresses, millimeter-wave radar
- Where
- Taiwan
- Volunteers
- 50 people
- Sponsor
- Fu Jen Catholic University
Colorectal Cancer Liver Metastasis
Prospective Validation of an AI Model for Predicting Liver Metastasis in Colorectal Cancer
This is a prospective, multicenter, observational study designed to validate the predictive accuracy of a pre-developed multimodal deep learning model.
- Trial name
- NCT07392567
- Testing
- Multimodal Deep Learning Prediction Model
- Where
- China
- Volunteers
- 160 people
- Sponsor
- Tongji Hospital
Pancreatic Adenocarcinoma
Multimodal Deep Learning Model Predicts Pancreatic Cancer Prognosis
This study describes the development and validation of a deep learning prediction model, which extracts deep learning features from preoperative enhanced CT scans and analyzes postoperative pathological specimens of pancreatic…
- Trial name
- NCT06760234
- Testing
- No Interventions
- Where
- China
- Volunteers
- 247 people
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Papillary Thyroid Carcinoma, Thyroid Neoplasms
RET-US Study - Ultrasound-Based Prediction of RET Alterations and Lateral-Neck Metastasis in Thyroid Cancer
Why is this study being done? RET gene alterations occur in only 5-10 % of papillary thyroid cancers, but they can change how surgeons treat the disease.
- Conditions
- Papillary Thyroid Carcinoma, Thyroid Neoplasms, RET Proto-Oncogene Mutation, Lymphatic Metastasis
- Trial name
- RET-US (NCT07042984)
- Testing
- AI-Ultrasound RET Prediction
- Where
- China
- Volunteers
- 800 people
- Sponsor
- Fujian Medical University
Breast Cancer, Axillary Lymph Node Metastasis
A Prospective Multicenter Study of the TuFEst-LN Model for Axillary Lymph Node Status Assessment in Breast Cancer
Through the research of this project, we expect to validate the clinical utility of the TuFEst-LN model in assessing axillary lymph node status in breast cancer patients.
- Trial name
- PRO-TuFEst-LN (NCT07304934)
- Testing
- No Intervention: Observational Cohort
- Where
- China
- Volunteers
- 400 people
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Glioma
Development and Validation of a Deep Learning-Based Survival Prediction Model for Pediatric Glioma Patients: A Retrospective Study Using the SEER Database and Chinese Data
Accurately predicting the survival of pediatric glioma patients is crucial for informed clinical decision-making and selecting appropriate treatment strategies.
- Trial name
- NCT06199388
- Testing
- Survival state
- Where
- China
- Volunteers
- 9,532 people
- Sponsor
- Tang-Du Hospital
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
Renal Cell Carcinoma, Kidney Neoplasms
Multimodal Prediction of Postoperative Prognosis After Partial Nephrectomy for Endophytic Renal Cell Carcinoma
This retrospective observational cohort study aims to develop and externally validate an imaging-clinical multimodal fusion model for predicting postoperative prognosis in patients with endophytic renal cell carcinoma undergoing…
- Conditions
- Renal Cell Carcinoma, Kidney Neoplasms, Endophytic Renal Tumor, Postoperative Renal Function
- Trial name
- PN-ProMM (NCT07697417)
- Testing
- Imaging-clinical multimodal prognostic modeling
- Where
- China
- Volunteers
- 406 people
- Sponsor
- Tianjin Medical University Second Hospital
Nasopharyngeal Cancinoma (NPC), Distant Metastasis
Development and Validation of a Deep Learning Model to Predict Distant Metastases in Nasopharyngeal Carcinoma Using Whole Slide Imaging and MRI
An AI model was developed to predict the likelihood of distant metastasis in patients with nasopharyngeal cancer based on pathology slides and MRI scans of the primary tumor.
- Trial name
- NCT06831357
- Where
- 2 sites in China
- Volunteers
- 500 people
- Sponsor
- Sun Yat-sen University
Endometrial Cancer
Developing a MRI-based Deep Learning Model to Predict MMR Status
In order to develop a convenient, cheap and comprehensive method to preoperatively predict dMMR and reduce the number of people requiring dMMR-related immunohistochemical or genetic testing after surgery, this study aims to…
- Trial name
- NCT05783986
- Testing
- randomly divided
- Volunteers
- 600 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Congenital Microtia
Deep Learning for Flap Perfusion Detection
The aim of this study is to develop a convolutional neural network-based image recognition model to identify flap perfusion abnormalities after first-stage auricular reconstruction in patients with congenital microtia.
- Trial name
- DL-FPA (NCT07846332)
- Testing
- AI-assisted remote monitoring of flap perfusion abnormalities after first-stage auricular reconstruction
- Where
- China
- Volunteers
- 232 people
- Sponsor
- Jing Xu
Ovarian Cancer
Artificial Intelligence Model for Growth Prediction of Ovarian Cancer Organoids
The present study aims to collect early bright field image of patient-derived organoids with ovarian cancer. By leveraging artificial intelligence, this study will seek to construct and refine algorithms that able to predict…
- Trial name
- NCT06317610
- Testing
- growth prediction of ovarian cancer organoids in the frame of bright field image by leveraging AI
- Where
- China
- Volunteers
- 100 people
- Sponsor
- Chongqing University Cancer Hospital
Hepatocellular Carcinoma, Chronic Liver Disease
Risk Stratification of Hepatocarcinogenesis Using a Deep Learning Based Clinical, Biological and Ultrasound Model in High-risk Patients
By 2030, hepatocellular carcinoma (HCC) will become the second leading cause of cancer-related death, accounting for more than one million deaths per year according to the World Health Organization.
- Trial name
- STARHE (NCT04802954)
- Testing
- Video acquisition
- Where
- 6 sites in France
- Volunteers
- 400 people
- Sponsor
- IHU Strasbourg
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