Clinical trials: Deep Learning Model, active
Non-small Cell Lung Cancer Metastatic
Predictive Multimodal Signatures Associated With Response to Treatment and Prognosis of Patients With Stage IV Non-small Cell Lung Cancer
Predicting response to therapy and disease progression in stage IV NSCLC patients treated with pembrolizumab monotherapy, chemotherapy-pembrolizumab combination therapy or chemotherapy alone in the first-line setting.
- Trial name
- DEEP-Lung-IV (NCT04994795)
- Testing
- Predictive models (data collection)
- Where
- 30 sites in United States, Brazil and 6 more
- Volunteers
- 4,000 people
- Sponsor
- Sophia Genetics SAS
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
Early Gastric Cancer
AI Model for Early Gastric Cancer Diagnosis Using Endoscopic Imaging
Early gastric cancer (EGC) is often difficult to detect accurately during endoscopic examination due to subtle morphological features and variability among endoscopists.
- Trial name
- XAI-EGC (NCT07551466)
- Testing
- No intervention (observational study)
- Where
- China
- Volunteers
- 100 people
- Sponsor
- The First Affiliated Hospital of Soochow University
Non-Small Cell Lung Cancer, Brain Metastases
Retrospective Multicenter Study of Patient-level T1CE/FLAIR MRI Deep Learning to Predict EGFR/ALK Driver Status in NSCLC Brain Metastases With External Validation and Survival Analysis
This retrospective multicenter observational study aims to develop and externally validate a noninvasive deep learning model based on routine brain MRI to identify actionable driver alterations in patients with non-small cell…
- Trial name
- DL-DriverBM (NCT07373951)
- Where
- China
- Volunteers
- 380 people
- Sponsor
- Ming Yang
Facet Joints; Degeneration ; Deep Learning ;Artificial Intelligence
Application of Multitask Deep Learning Model in Grading the Severity of Spinal Facet Joint Degeneration
Spinal facet joint osteoarthritis is a disease with high incidence among people over 40 years old. It is a disease characterized by a series of degenerative pathological changes and clinical features of synovium, articular…
- Trial name
- NCT05635006
- Where
- China
- Volunteers
- 1,132 people
- Sponsor
- Hai Lv
Nasopharyngeal Carcinoma, Herpesvirus 4, Human
Deep Learning-based sbORN Diagnostic Model
Skull-base osteonecrosis (sbORN) is a severe long-term complication of nasopharyngeal carcinoma (NPC) post radiotherapy, which significantly diminish the quality of life, increase the risk of internal carotid artery rupture, and…
- Trial name
- NCT06463392
- Testing
- No Intervention: Observational Cohort
- Where
- China
- Volunteers
- 312 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen 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
Metabolic Dysfunction-Associated Steatotic Liver Disease, Hepatic Steatosis
Quantitative Ultrasound (RS85 and R20) for Liver Fat Quantification in MASLD Using MRI-PDFF as Reference
This multicenter prospective study aims to evaluate the correlation between quantitative ultrasound fat fraction (USFF) and MRI-PDFF (Proton Density Fat Fraction) for liver fat quantification in patients with metabolic…
- Conditions
- Metabolic Dysfunction-Associated Steatotic Liver Disease, Hepatic Steatosis, Liver Disease Parenchymal
- Trial name
- DeepUSFF (NCT07192159)
- Testing
- Quantitative ultrasound (DeepUSFF)
- Where
- 2 sites in United States, South Korea
- Volunteers
- 182 people
- Sponsor
- Seoul National University Hospital
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
Ovarian Cancer, Ovarian Tumor
AI Analysis of CT Scans to Classify Ovarian Tumours as Benign, Borderline or Malignant Before Surgery
The goal of this observational study is to learn if a computer program can tell what type of ovarian tumour a person has from a CT scan taken before surgery. The program uses artificial intelligence (AI).
- Conditions
- Ovarian Cancer, Ovarian Tumor, Borderline Ovarian Tumor
- Trial name
- OvaClass (NCT07883551)
- Where
- 7 sites in Belgium, Netherlands
- Volunteers
- 1,300 people
- Sponsor
- Catharina Ziekenhuis Eindhoven
Accuracy of Root Canal Curvature Analysis
Development and Diagnostic Accuracy of a Deep Learning Model for Root Canal Curvature Analysis in Mandibular Molars Using CBCT Scans: A Diagnostic Accuracy Study
Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve…
- Trial name
- NCT07587060
- Where
- Egypt
- Volunteers
- 207 people
- Sponsor
- Cairo University
Pancancer
Prospective Pathology Foundation Models
Histopathology remains the gold standard for disease diagnosis, yet faces challenges including pathologist shortages and diagnostic model limitations.
- Trial name
- NCT07157618
- Where
- 2 sites in China
- Volunteers
- 2,000 people
- Sponsor
- Nanfang Hospital, Southern Medical University
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
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
T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration
Multimodal Deep Learning for Lymph Node Metastasis Prediction and Physician Performance Assessment in T1 Gastric Cancer
This study aims to develop and validate an artificial intelligence (AI) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric…
- Trial name
- NCT07124754
- Testing
- Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric Cancer
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Qun Zhao
Gastric Cancer (Diagnosis), Postoperative Complications
DeepComp for Prediction of Gastric Cancer Postoperative Complications (DeepComp-Prospective)
Gastric cancer is a leading cause of cancer-related mortality, and radical surgery remains the primary treatment. However, postoperative complications are common and can significantly impact patient recovery and quality of life.
- Trial name
- NCT07401173
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Qun Zhao
Sleep-Disordered Breathing, Sleep Architecture
Validation of Belun Ring Gen3 Deep Learning Algorithms With Subxiphoid Body Sensor
Hypothesis: BR's Gen3 DL algorithms, combined with its subxiphoid body sensor, can accurately diagnose OSA, categorize its severity, identify REM OSA and supine OSA, and detect central sleep apnea (CSA).
- Conditions
- Sleep-Disordered Breathing, Sleep Architecture, Arrhythmia
- Trial name
- NCT06255613
- Testing
- Belun Ring, Belun Cor
- Where
- 2 sites in United States
- Volunteers
- 79 people
- Sponsor
- Belun Technology Company Limited
Pulmonary Nodules, Early Detection of Cancer
Diagnostic Performance of an AI-Based Multi-Omics Model for Early Lung Cancer
This is a prospective, multicenter observational cohort study for patients with lung nodules suspicious for early-stage lung cancer.
- Conditions
- Pulmonary Nodules, Early Detection of Cancer, Lung Neoplasms
- Trial name
- NCT07882628
- Where
- 8 sites in China
- Volunteers
- 1,050 people
- Sponsor
- Beijing Chao Yang Hospital
Carotid Stenosis
Risk Prediction Model for Cerebrovascular Events in Carotid Artery Stenosis
Atherosclerotic carotid artery stenosis is a major cause of stroke, and early identification of high-risk patients combined with surgical intervention can significantly reduce stroke risk.
- Trial name
- NCT06452173
- Testing
- Plasma, carotid high-resolution magnetic resonance imaging
- Where
- China
- Volunteers
- 300 people
- Sponsor
- Beijing Tiantan Hospital