Clinical trials: Deep Learning Model
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
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
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
COVID-19 (Coronavirus Disease 2019), COVID-19 Pneumonia
Convolutional Neural Network Model to Detect Coronavirus Disease 2019 (COVID-19) Pneumonia in Chest Radiographs
This study aims to design a Convolutional Neural Network (CNN) and apply an attention model to help differentiate pneumonia due to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pneumonia due to other…
- Trial name
- RedNeumon (NCT05722665)
- Testing
- Categorization of chest xrays images
- Where
- Colombia
- Volunteers
- 3,599 people, healthy volunteers welcome
- Sponsor
- Fundacion Clinica Valle del Lili
Small for Gestational Age Infant, Fetal Growth Restriction
Developing and Testing AI Models for Fetal Biometry and Amniotic Volume Assessment in Fetal Ultrasound Scans.
Routine fetal ultrasound scan during the second trimester of the pregnancy is a low-cost, noninvasive screening modality that has been proven to lower fetal mortality by up to 20%.
- Conditions
- Small for Gestational Age Infant, Fetal Growth Restriction, Oligohydramnios, Polyhydramnios
- Trial name
- NCT05059093
- Testing
- Classification and segmentation deep learning models
- Where
- 6 sites in Morocco
- Volunteers
- 122 people, healthy volunteers welcome
- Sponsor
- Deepecho
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
Artificial Intelligence (AI), Deep Learning
The Construction and Effect Verification of a Deep Learning-based Automated Semantic Segmentation Model for Medical Imaging
Hepatocellular Carcinoma(HCC) is a common disease in China, ranking as the fourth most prevalent malignant tumor and the third leading cause of cancer-related deaths in the country.
- Conditions
- Artificial Intelligence (AI), Deep Learning, Laparoscopic Surgery
- Trial name
- NCT06864702
- Testing
- Whether the patient received diagnosis and treatment at Zhujiang Hospital of Southern Medical University and retained medical images such as abdominal
- Where
- China
- Volunteers
- 220 people, healthy volunteers welcome
- Sponsor
- Zhujiang Hospital
BIS, BIS-EEG
Deep Learning Framework for Continuous Depth of Anesthesia Forecasting
The integration of Artificial Intelligence (AI) in anesthesiology offers the potential to shift patient monitoring from reactive to predictive.
- Conditions
- BIS, BIS-EEG, Artifical Intelligence, Intraoperative
- Trial name
- NCT07536230
- Where
- Belgium
- Volunteers
- 115 people, healthy volunteers welcome
- Sponsor
- Universitair Ziekenhuis Brussel
Artificial Intelligence
The Accuracy of Detection of Artificial Intelligence Second Mesio-buccal Canal of Maxillary First Molars on CBCT Images
CAD systems are computer applications that assist in the detection and/or diagnosis of diseases by providing an unbiased "second opinion" to the image interpreter, aiming at improving accuracy and reducing time for analysis.
- Trial name
- NCT05340140
- Testing
- deep learning model
- Where
- Egypt
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- Cairo University
Breast Cancer
Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization
The correct categorization of breast density is essential to adapt the diagnostic examination to the needs of each patient. Assessment of breast density is performed visually by radiologists.
- Trial name
- NCT05021055
- Volunteers
- 277 people, healthy volunteers welcome
- Sponsor
- Hospital Italiano de Buenos Aires
Heart Failure, Cardiomyopathies
Multimodal Physiologic State Intelligence Study
The OMNIPHYS study will investigate whether multimodal ultrasound and other routinely collected clinical and physiologic data can be combined with artificial intelligence to characterize changes in a person's physiologic state…
- Conditions
- Heart Failure, Cardiomyopathies, Pulmonary Hypertension, Myocarditis; Acute or Subacute
- Trial name
- OMNIPHYS (NCT07814118)
- Testing
- OMNIPHYS Multimodal Ultrasound Imaging System
- Where
- United States
- Volunteers
- 25,000 people, healthy volunteers welcome
- Sponsor
- Truway Health, Inc.
Knowledge, Satisfaction
Deep Learning Model Detecting Pressure Injury
In the health care system, pressure injuries, which are among the quality indicators, are a serious patient safety problem that affects the length of hospital stay and the cost of care.
- Trial name
- NCT06641258
- Testing
- Control Group (Standard Procedure), Experimental Group
- Where
- Turkey (Türkiye)
- Volunteers
- 60 people, healthy volunteers welcome
- Sponsor
- University of Beykent
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
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
Peripheral Vein, Arterial Wave Reflections
Deep Learning Model for Predicting a Peripheral Venous Waveform-based Pulse Pressure Variation
Pulse pressure variation is a monitoring index that indicates the response to fluid therapy in patients receiving mechanical ventilation, and is used as a reference for patients with unstable hemodynamic conditions.
- Conditions
- Peripheral Vein, Arterial Wave Reflections, Pulse Pressure Variation, Stroke Volume Variation
- Trial name
- NCT06734650
- Testing
- peripheral waveform collection
- Where
- South Korea
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Seoul National University Bundang Hospital
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
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
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
Dental Plaque (Diagnosis), Deep Learning
Microbial Dental Plaque Analysis in Young Permanent Teeth Using Deep Learning
Background: Dental plaque contributes to a number of common oral conditions such as caries, gingivitis, and periodontitis. As a result, detection and management of plaque is of great importance for the oral health of individuals.
- Trial name
- NCT06603233
- Testing
- The Difference Between The AI Model and Dentists Group, Deep Learning Models
- Where
- Turkey (Türkiye)
- Volunteers
- 31 people, healthy volunteers welcome
- Sponsor
- Ankara Medipol University
Dementia (Diagnosis), Alzheimer Dementia (AD)
Speech-Based Artificial Intelligence for Detection of Dementia in Danish Patients (DetectAI)
The goal of this observational study is to learn if an artificial intelligence (AI)-based speech analysis tool can identify which patients with memory problems need specialist evaluation at a memory clinic.
- Conditions
- Dementia (Diagnosis), Alzheimer Dementia (AD), Vascular Dementia (VaD), Lewy Body Dementia (LBD)
- Trial name
- DetectAI (NCT07200739)
- Testing
- Mini-mental State Examination, Addenbrooke's Cognitive Examination, Speech Task - Picture Description
- Where
- Denmark
- Volunteers
- 440 people, healthy volunteers welcome
- Sponsor
- Zealand University Hospital