Clinical trials: Deep Learning
Pulmonary Nodules, Multiple
Detection and Volumetry of Pulmonary Nodules on Ultra-low Dose Chest CT Scan With Deeplearning Image Reconstruction Algorithm (DLIR)
evaluate the diagnostic performance of ultra-low dose CT using deep learning-based reconstruction in the detection of pulmonary nodules.
- Trial name
- DLIRTHORAX (NCT04482114)
- Testing
- ULD CT
- Where
- France
- Volunteers
- 70 people, healthy volunteers welcome
- Sponsor
- Centre Hospitalier Universitaire, Amiens
Artificial Intelligence
Application Value of Deep Learning in Diagnosis of Cervical Spondylosis
Compared with the personal experience judgment of physicians, deep learning can identify something more quickly, efficiently, and accurately The identification and diagnosis of diseases save the energy of clinical and imaging…
- Trial name
- NCT04952233
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Breast Cancer
Using Deep Learning Methods to Analyze Automated Breast Ultrasound and Hand-held Ultrasound Images, to Establish a Diagnosis, Therapy Assessment and Prognosis Prediction Model of Breast Cancer.
The purpose of this study is using a deep learning method to analyze the automated breast ultrasound (ABUS) and hand-held ultrasound(HHUS) images, establish and evaluate a diagnosis, therapy assessment and prognosis prediction…
- Trial name
- NCT04270032
- Testing
- ABUS and HHUS
- Where
- China
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- The First Affiliated Hospital of the Fourth Military Medical University
Parkinson Disease
EEG Recordings and Analysis in Parkinson's Patients: Towards Adaptive Deep Brain Stimulation by Machine Learning
The objective of this protocol is to obtain on Parkinson's disease more accessible therapeutic targets than deep brain stimulation (HFS-STN), the neurosurgical treatment for this pathology.
- Trial name
- ElectroPARK (NCT05284526)
- Testing
- electroencephalogram (EEG) of control and parkinsonian subjects during the preparation and execution of movements
- Where
- France
- Volunteers
- 30 people, healthy volunteers welcome
- Sponsor
- Assistance Publique - Hôpitaux de Paris
Blinking, Deep Learning
Development and Validation of Deep Neural Networks for Blinking Identification and Classification
Primary objective of this study is the development and validation of a system of deep neural networks which automatically detects and classifies blinks as "complete" or "incomplete" in image sequences.
- Trial name
- NCT04828187
- Testing
- Comparison of the proposed artificial network with the ground truth
- Where
- 2 sites in Greece
- Volunteers
- 8 people, healthy volunteers welcome
- Sponsor
- Democritus University of Thrace
Scoliosis Idiopathic Adolescent, Scoliosis
Deep Learning for Early Scoliosis Detection Using mmWave Radar Gait Data
Scoliosis is a sideways curvature of the spine that often develops during childhood and adolescence. When detected early, scoliosis can be managed effectively with non-invasive approaches such as bracing and physiotherapy, while…
- Trial name
- ScoliRadar-AI (NCT07593560)
- Testing
- mmWave Radar Gait Assessment
- Where
- Turkey (Türkiye)
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Gebze Technical University
Non-small Cell Lung Cancer, Spread Through Air Space
Deep Learning Signature for Predicting Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer
The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting aggressive histological pattern in resected non-small cell lung cancer based on a multicenter prospective cohort.
- Conditions
- Non-small Cell Lung Cancer, Spread Through Air Space, Visceral Pleural Invasion, Lymphovascular Invasion
- Trial name
- NCT05925738
- Testing
- PET/CT-based Deep Learning Signature
- Where
- 3 sites in China
- Volunteers
- 1,500 people, healthy volunteers welcome
- Sponsor
- Shanghai Pulmonary Hospital, Shanghai, China
Cancer Diagnosis, Liver Cancer, Adult
Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening.
- Conditions
- Cancer Diagnosis, Liver Cancer, Adult, Cancer Screening, Colorectal Cancer (CRC)
- Trial name
- NCT06822413
- Testing
- No Interventions
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Ophthalmology, Artificial Intelligence (AI)
Detection of Systemic Diseases Such as Hepatobiliary Diseases From Ocular Images Via Deep Learning
Oculomics is an emerging interdisciplinary field that deciphers multi-dimensional, high-throughput ocular data to predict, diagnose, and monitor systemic diseases and health span.In recent years, artificial Intelligence may…
- Conditions
- Ophthalmology, Artificial Intelligence (AI), Hepatobiliary Diseases, Systemic Diseases
- Trial name
- NCT07581925
- Testing
- Systemic diseases such as Hepatobiliary Disorders
- Where
- China
- Volunteers
- 730 people, healthy volunteers welcome
- Sponsor
- Zhongshan Ophthalmic Center, Sun Yat-sen University
Heart Failure, Heart Failure With Preserved Ejection Fraction
PACIFIC-PRESERVED : PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunction - HF With PRESERVED LVEF Study
This is a prospective multicenter study to decipher phenotypic variability within patients with heart failure and preserved left ventricular ejection fraction (HFpEF).
- Trial name
- NCT04189029
- Testing
- Extensive phenotyping
- Where
- France
- Volunteers
- 175 people, healthy volunteers welcome
- Sponsor
- Assistance Publique - Hôpitaux de Paris
PechaKucha Presentation, Traditional PowerPoint Presentation
Effect of PechaKucha (PK)Presentation Method on Nursing Students' Satisfaction Level With Deep Breathing and Cough Exercise Skills and Education Method
ABSTRACT Aim: The aim of this study is to examine the effect of the PK presentation method on nursing students' deep breathing and cough exercise skills and the students' level of satisfaction with this method.
- Trial name
- NCT06862024
- Testing
- Deep Breathing and Cough Exercise Skills, Satisfaction with the training method
- Where
- Turkey (Türkiye)
- Volunteers
- 96 people, healthy volunteers welcome
- Sponsor
- Eastern Mediterranean University
Lymph Nodes With Tumor Metastasis
Predicting Tumor Origin Based on Deep Learning of Lymph Node Puncture Cytology
In this study, the investigators aimed to construct a deep learning diagnostic model that uses cytological images to predict primary unknown tumor origins in patients with tumors combined with lymph node metastases.
- Trial name
- NCT06810349
- Where
- China
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- West China Hospital
Labrum Injury of the Hip Joint
Research on Acetabular Labrum Injury Based on MR: Multi-angle Deep Learning Model
The purpose of this study is to study the MRI images of acetabular labrum injury by deep learning method, and try to establish a combination model of axial and coronal serial images, and compare with the diagnostic accuracy of…
- Trial name
- NCT04950036
- Testing
- Diagnostic Test
- Where
- China
- Volunteers
- 1,261 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Congenital Heart Disease
Interpretation of Fetal Echocardiography by Artificial Intelligence
The study to be performed aims to design and develope an automated Intelligent Decision Support System for fetal echocardiography that can significantly assist the obstetric physician in the improvement of detection of fetal…
- Trial name
- LIFE (NCT05090306)
- Testing
- Routine ultrasound examination
- Where
- Romania
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- University of Medicine and Pharmacy Craiova
Breast Cancer Related Lymphedema, Deep Learning
Study on Classification Method of Indocyanine Green Lymphography Based on Deep Learning
Breast cancer related lymphedema (BCRL) is the most common complication after breast cancer surgery, which brings a heavy psychological and spiritual burden to patients.
- Trial name
- BCRL；ICG (NCT04824378)
- Testing
- No Intervention.
- Where
- China
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital
Heart Failure
Deep Learning-Based Automated Pressure-Strain Loop Analysis
Noninvasive left ventricular pressure-strain loop analysis estimates myocardial work from longitudinal strain, brachial systolic blood pressure, and cardiac valve-event timing.
- Trial name
- NCT07850726
- Testing
- Sustained Isometric Handgrip Exercise, Semi-Supine Bicycle Exercise
- Where
- Norway
- Volunteers
- 25 people, healthy volunteers welcome
- Sponsor
- Norwegian University of Science and Technology
AKI, Therapeutic Drug Monitoring (TDM)
Research on the Risk Warning Model and Prevention Strategies for Acute Kidney Injury Associated With Cyclosporine Based on Explainable Deep Neural Networks and Therapeutic Drug Monitoring
In this study, the investigators will focus on hospitalized patients using cyclosporine and develop an acute kidney injury risk prediction model through in-depth analysis of electronic medical record data, employing interpretable…
- Trial name
- NCT06596811
- Where
- China
- Volunteers
- 1,200 people, healthy volunteers welcome
- Sponsor
- Qianfoshan Hospital
Ovarian Cancer
Ovarian Cancer Identification on CT Using Deep Learning
Ovarian cancer remains the deadliest gynecologic malignancy, with poor survival rates largely due to late-stage diagnosis. Early detection is crucial, yet no universally accepted screening method exists.
- Trial name
- NCT06851429
- Where
- 2 sites in Taiwan
- Volunteers
- 12,578 people, healthy volunteers welcome
- Sponsor
- Chang Gung Memorial Hospital
Motor Development Assessment, Artificial Intelligence-Based Movement Analysis
AI-Based Video Analysis for Motor Development Assessment in Children
This is a non-interventional, prospective observational study aimed at developing and validating an artificial intelligence-based system for assessing motor development in children using video analysis.
- Trial name
- AMD-AI (NCT07597356)
- Testing
- Observational Assessment Only
- Where
- Turkey (Türkiye)
- Volunteers
- 60 people, healthy volunteers welcome
- Sponsor
- Medipol University
Colorectal Neoplasms, Colonic Polyp
Effectiveness of Artificial Intelligence-Assisted Colonoscopy for Adenoma Detection in Routine Clinical Practice : a Prospective Multicenter Randomized Trial
This study is a multi-center, randomized controlled trial designed to evaluate whether an artificial intelligence (AI) system can assist endoscopists to improve the detection rate of colorectal adenomas and cancers during…
- Conditions
- Colorectal Neoplasms, Colonic Polyp, Adenoma, Colorectal Cancer
- Trial name
- AI-COLOADR (NCT07307547)
- Testing
- AI-Assisted Colonoscopy
- Where
- China
- Volunteers
- 3,300 people, healthy volunteers welcome
- Sponsor
- Zhejiang University