Clinical trials: Deep Learning
Bladder Cancer, Staging
Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
Bladder cancer is the most common malignant tumor of the urinary system. The presence or absence of muscle invasion in early bladder cancer is an independent prognostic factor.
- Conditions
- Bladder Cancer, Staging, Deep Learning, Neoadjuvant Chemotherapy
- Trial name
- MICS-BC (NCT07051083)
- Testing
- Risk Stratification
- Where
- China
- Volunteers
- 480 people
- Sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Diabetic Retinopathy, Diabetic Eye Problems
Detection and Classification of Diabetic Retinopathy From Posterior Pole Images With A Deep Learning Model
The duration of diabetes is directly related to eye complications. Diabetic retinopathy affects 80 percent of those who have had diabetes for 20 years or more.
- Conditions
- Diabetic Retinopathy, Diabetic Eye Problems, Diabetic Macular Edema
- Trial name
- NCT04805541
- Testing
- Color Fundus Photography, Mydriatic Agent, EyeCheckup - AI Based DR Screening
- Where
- Turkey (Türkiye)
- Volunteers
- 900 people
- Sponsor
- Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi
Idiopathic Pulmonary Fibrosis, Interstitial Lung Disease
Validation of AI-Based Detection of Idiopathic Pulmonary Fibrosis in Serial Chest Radiographs: A Retrospective Longitudinal Study
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disease of unknown cause with a median survival of only 3-5 years after diagnosis.
- Trial name
- NCT07712952
- Testing
- VUNO Med-Chest X-ray
- Where
- South Korea
- Volunteers
- 175 people
- Sponsor
- Chung-Ang University Hospital
Age Problem, Fall
Fall Risk Assessment Using Hybrid Machine Learning and Deep Learning Approaches and a Novel Posturography
The purpose of this project is to combine a novel posturogrpahy based on HTC VIVE trackers and hybrid machine learning and deep learning algorithms to establish a set of simple, convenient and valid fall risk assessment tool.
- Trial name
- NCT05308563
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- National Taiwan University Hospital
Liver Fibrosis
Prediction of Significant Liver Fibrosis
The deep learning method based on convolutional neural network (CNN) was used to extract the relevant features of liver fibrosis classification from the multi-modal information of digital pathological sections, clinical…
- Trial name
- PSLF (NCT06509230)
- Where
- China
- Volunteers
- 700 people, healthy volunteers welcome
- Sponsor
- Huang Haijun
Non-small Cell Lung Cancer
Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer
The purpose of this study is to evaluate the performance of a PET/CT-based deep learning signature for predicting occult nodal metastasis of clinical stage N0 non-small cell lung cancer in a multicenter prospective cohort.
- Trial name
- NCT05425134
- Testing
- PET/CT-based Deep Learning Signature
- Where
- 4 sites in China
- Volunteers
- 5,000 people
- Sponsor
- Shanghai Pulmonary Hospital, Shanghai, China
Neurodegenerative Diseases, Aging
Simulation-informed Modelling and Personalized Evaluation (SIMPLE) in Ageing Populations
Multimodal magnetic resonance imaging (MRI), detecting brain structural and functional changes, has emerged as a powerful and promising technique to study individual's brain, as T1-weighted scans can detect morphometric features…
- Conditions
- Neurodegenerative Diseases, Aging, Brain, Cognitive Dysfunction
- Trial name
- NCT06572332
- Where
- Hong Kong
- Volunteers
- 300 people, healthy volunteers welcome
- Sponsor
- Chinese University of Hong Kong
Venous Thromboembolism, Deep Venous Thrombosis
Education Bundle to Decrease Patient Refusal of VTE Prophylaxis
The investigators have recently developed a registry of missed doses of VTE prophylaxis that includes retrospective data on missed doses of VTE prophylaxis.
- Conditions
- Venous Thromboembolism, Deep Venous Thrombosis, Pulmonary Embolism
- Trial name
- NCT02402881
- Testing
- Patient-centered education bundle
- Where
- United States
- Volunteers
- 19,652 people
- Sponsor
- Johns Hopkins University
Abdominal Pain, Acute Pain
Diagnostic Performance of Low-Dose CT for Acute Abdominal Conditions
The goal of this non-inferiority observational study is to assess the diagnostic performance of low-dose CT with deep learning image reconstruction (DLIR) in adult participants with acute abdominal conditions.
- Conditions
- Abdominal Pain, Acute Pain, Acute Cholecystitis, Acute Appendicitis
- Trial name
- DETECT_Acute (NCT05651360)
- Testing
- low-dose CT
- Where
- 2 sites in Denmark, Norway
- Volunteers
- 246 people
- Sponsor
- Oslo University Hospital
Skin Cancer, Melanoma
AI-Augmented Skin Cancer Diagnosis in Teledermatoscopy
In this study an artificial intelligence (AI) tool for skin cancer diagnosis is implemented in a teleldermatoscopy platform. The aim is to study the effects on clinician diagnostic accuracy, management decisions, and confidence.
- Trial name
- AIDMel (NCT06080711)
- Testing
- AI assistance
- Where
- Sweden
- Volunteers
- 30 people, healthy volunteers welcome
- Sponsor
- Karolinska University Hospital
Renal Tumor, Kidney Neoplasm
An MRI-Based Study of Intelligent Pathological Subtyping and Grading of Renal Tumors
This retrospective + prospective, non-interventional study aims to develop and evaluate artificial intelligence methods for the detection, pathological subtyping, and histological grading of renal tumors using magnetic resonance…
- Trial name
- NCT07743749
- Testing
- MRI-Based Artificial Intelligence Analysis
- Where
- China
- Volunteers
- 900 people
- Sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Elective Thoracic Surgery, Pulmonary Function
Deep Learning for Preoperative Pulmonary Assessment in Thoracic CT
The trial was designed as a single-centre, non-interventional prospective observational study to utilize deep learning technology combined with computed tomography (CT) images to precisely predict the pulmonary function…
- Conditions
- Elective Thoracic Surgery, Pulmonary Function, Deep Learning
- Trial name
- NCT06477458
- Testing
- Single inspiratory phase computed tomography., Respiratory dual-phase computed tomography.
- Where
- China
- Volunteers
- 2,000 people
- Sponsor
- The First Affiliated Hospital of Guangzhou Medical University
Preeclampsia, Preeclampsia Severe
Risk Prediction Model of Preeclampsia
Preeclampsia is the main cause of increased maternal and perinatal mortality during pregnancy. Preeclampsia is mainly manifested as hypertension, urine protein, or damage symptoms of other target organs after 20 weeks of…
- Trial name
- NCT04794855
- Testing
- laboratory tests
- Where
- China
- Volunteers
- 2,000 people
- Sponsor
- Peking University Third Hospital