Clinical trials: Artificial Intelligence in Education
COVID-19, Acute Kidney Injury
Applying Artificial Intelligence to Identify Subphenotypes of Acute Kidney Injury in Mexican Patients With Severe COVID-19
The goal of this observational study was to identify subphenotypes of acute kidney injury patients with COVID-19, and the investigators analyzed their impact on mortality.
- Trial name
- IA-COVAKI (NCT06471101)
- Testing
- clusters
- Where
- Mexico
- Volunteers
- 2,934 people
- Sponsor
- Instituto Nacional de Enfermedades Respiratorias
Pediatric ALL, Sepsis
Evaluation of Pediatric eCART Implementation
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical…
- Trial name
- NCT06771830
- Testing
- Pediatric eCART
- Where
- United States
- Volunteers
- 30,000 people
- Sponsor
- University of Wisconsin, Madison
Electrocardiogram Interpretation, Nursing Education
Innovative Electrocardiogram Training Using Artificial Intelligence Clinical Scenarios for Nursing Staff
Background and Purpose Accurate interpretation of an Electrocardiogram is a vital skill for nursing staff to ensure patient safety and timely intervention in cardiovascular care.
- Conditions
- Electrocardiogram Interpretation, Nursing Education, Clinical Reasoning, Artificial Intelligence
- Trial name
- NCT07455357
- Testing
- Artificial Intelligence Driven Scenario-Based Learning Software, Traditional Electrocardiogram Educational Program
- Where
- Egypt
- Volunteers
- 64 people, healthy volunteers welcome
- Sponsor
- Alexandria University
Colorectal Cancer, Colorectal Neoplasms
Early Detection of Advanced Adenomas and Colorectal Cancer
This study aims to develop a highly sensitive, specific, and cost-effective blood assay for early detection of colorectal adenomas and cancer, using advanced machine learning and state-of-the-art biological analyses.
- Conditions
- Colorectal Cancer, Colorectal Neoplasms, Colorectal Polyp, Colorectal Adenocarcinoma
- Trial name
- AACRC (NCT06342440)
- Testing
- DENEB
- Where
- 6 sites in United States, China and 3 more
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- City of Hope Medical Center
Crohn Disease
AI-enabled Endoscopic Prediction of Post-operative Recurrence in Crohn's Disease
This is a multicentre prospective international observational study. This study aims to introduce a novel multidimensional approach to precision imaging, enabling the identification and stratification of high-risk patients who…
- Trial name
- PROSPER (NCT06505304)
- Testing
- Colonoscopy, Intestinal biopsies, Confocal laser endomicroscopy
- Where
- 15 sites in Belgium, Canada and 4 more
- Volunteers
- 225 people
- Sponsor
- University College Cork
Alzheimer Disease (AD)
Generation of Synthetic [18F]FDG PET From Early-Phase Amyloid PET in Alzheimer's Disease
This study aims to test a new artificial intelligence (AI) method to create brain scan images without needing an extra scan. Currently, patients with memory problems often undergo two types of PET scans (Amyloid PET and FDG PET)…
- Trial name
- NCT07431255
- Where
- Italy
- Volunteers
- 35 people
- Sponsor
- IRCCS San Raffaele
Hepatocellular Carcinoma (HCC)
STRATHEP: AI-Driven Treatment Stratification for Advanced Hepatocellular Carcinoma
STRATHEP develops and validates a multimodal AI model to predict treatment response in advanced hepatocellular carcinoma. By integrating digital pathology and MRI radiomics, the project identifies patients likely to benefit from…
- Trial name
- STRATHEP (NCT07863258)
- Where
- 5 sites in Belgium
- Volunteers
- 280 people
- Sponsor
- Universitaire Ziekenhuizen KU Leuven
Type 1 Diabetes Mellitus, Diabetes Self-Management Education
DiaBuddy: AI-Enabled Digital Self-Management for Youth With Type 1 Diabetes
The goal of this clinical trial is to learn whether DiaBuddy, a digital self-management app, can help children and adolescents with Type 1 diabetes better manage their condition and reduce the burden experienced by their…
- Conditions
- Type 1 Diabetes Mellitus, Diabetes Self-Management Education, Caregiver Burden
- Trial name
- DiaBuddy (NCT07861373)
- Testing
- DiaBuddy: AI-Enabled Digital Self-Management Intervention, Usual Diabetes Care
- Volunteers
- 140 people
- Sponsor
- Dr. Juwayria Omar
CNS Tumor
Artificial Intelligence in CNS Radiation Oncology
Radiotherapy involves the use of high-energy X-rays, which can be used to stop the growth of tumor cells. Radiotherapy constitutes an essential avenue in the treatment of brain tumors.
- Trial name
- AI-RAD (NCT06036394)
- Testing
- The images (CT, MRI, PET) used for RT planning, mid-treatment imaging as part of IGRT or disease evaluation, and response assessment/ surveillance post-RT
- Where
- India
- Volunteers
- 6,000 people
- Sponsor
- Tata Memorial Centre
Chatbot-Based Training, Hemodialysis
DialysisBot: AI Chatbot for Hemodialysis Self-Management
End-stage kidney disease requiring hemodialysis is a chronic condition with substantial clinical, functional, and psychosocial burden.
- Conditions
- Chatbot-Based Training, Hemodialysis, Self-management
- Trial name
- NCT07830810
- Testing
- DialysisBot
- Where
- Italy
- Volunteers
- 40 people
- Sponsor
- University of Rome Tor Vergata
Alzheimer Disease, Alzheimer's Disease (Incl Subtypes)
Prediction of Amyloid and Mild Cognitive Impairment in Early Stage Alzheimer's Disease From Remote Speech Phenotyping
The S22 study investigates, in a cross-sectional study, the ability of algorithms that analyse acoustic and linguistic patterns of spoken language to predict the presence of amyloid positivity in early stage Alzheimer's disease…
- Conditions
- Alzheimer Disease, Alzheimer's Disease (Incl Subtypes), Mild Cognitive Impairment
- Trial name
- EARS (NCT04928690)
- Volunteers
- 140 people
- Sponsor
- Novoic Limited
HCC, Liver Cancer
Artificial Intelligence vs. LIRADS in Diagnosing HCC on CT
Liver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer death worldwide. It is the 3rd most common cause of cancer death in Hong Kong.
- Trial name
- NCT04843176
- Testing
- Prototype artificial intelligence algorithm, LI-RADS
- Where
- Hong Kong
- Volunteers
- 250 people
- Sponsor
- The University of Hong Kong
Liver Transplant Disorder, Self Efficacy
Effectiveness of Intelligent Case Manage Platform in Liver Transplant Recipients
This study is a prospective, quasi-experimental design, with an experimental group and a control group, will be created. The aims of this study are as follows: 1.
- Conditions
- Liver Transplant Disorder, Self Efficacy, Quality of Life
- Trial name
- ICMP (NCT05953948)
- Testing
- Intelligent Case Manage Platform (ICMP) and self-management program
- Where
- Taiwan
- Volunteers
- 333 people
- Sponsor
- Chang Gung University
Autism Spectrum Disorder, Attention Deficit Disorder With Hyperactivity (ADHD)
Pai.ACT: AI-Driven ACT Chatbot for Mental Health Triage and Service Evaluation
Parents of children with special needs in Hong Kong often face limited psychological support, which can negatively impact the child rehabilitation process and the well-being of parent-child relationships.
- Conditions
- Autism Spectrum Disorder, Attention Deficit Disorder With Hyperactivity (ADHD), Neurodevelopmental Disorder (Diagnosis), Dyslexia
- Trial name
- NCT06808555
- Testing
- Pai.ACT Group, Control Group
- Where
- 20 sites in Hong Kong
- Volunteers
- 340 people, healthy volunteers welcome
- Sponsor
- Chinese University of Hong Kong
Keywords: Artificial Intelligence, Bowel Preparation, Colonoscopy, Smartphone Application, Bowel Preparation for Colonoscopy
The Effectiveness of Bowel Preparation in Colonoscopy Patients Using Artificial Intelligence-assisted Nursing Education
Background: Colonoscopy is a critical diagnostic and screening tool for colorectal cancer, and its effectiveness largely depends on bowel preparation quality.
- Trial name
- NCT07791641
- Testing
- The effectiveness of bowel preparation in colonoscopy patients using artificial intelligence-assist, rountine care
- Where
- Taiwan
- Volunteers
- 140 people
- Sponsor
- Evian Lin
Artificial Intelligence (AI), Clinical Reasoning
Learning Diagnostic Reasoning Through AI
This experiment aims to determine the effect of AI-generated questions and feedback on diagnostic reasoning in preclinical medical students.
- Conditions
- Artificial Intelligence (AI), Clinical Reasoning, Medical Education, Feedback
- Trial name
- NCT06754826
- Testing
- AI-generated questions and feedback as a spaced repetition
- Where
- Turkey (Türkiye)
- Volunteers
- 71 people, healthy volunteers welcome
- Sponsor
- Gazi University
Crohn's Disease
Artificial Intelligence-Based Classification and Prognostic Prediction in Small Bowel Crohn's Disease
This retrospective observational study aims to develop an artificial intelligence-based system for the precise classification and prognostic prediction of small bowel Crohn's disease.
- Trial name
- NCT07757217
- Testing
- Artificial Intelligence-Based Multimodal Analysis
- Where
- China
- Volunteers
- 437 people
- Sponsor
- Shanghai 10th People's Hospital
Deep Learning
A New Deep-learning Based Artificial Intelligence Iterative Reconstruction (AIIR) Algorithm in Low-dose Liver CT
CT-enhanced scans are routine imaging modality for the diagnosis and follow-up of liver disease. However, this means that patients will receive more radiation dose.
- Trial name
- NCT05550012
- Testing
- low-dose CT
- Where
- China
- Volunteers
- 100 people
- Sponsor
- Qianfoshan Hospital
Breast Cancer
Artificial Intelligence and Machine Learning to Guide CDK4/6 Inhibitor Rechallenge in Breast Cancer.
The goal of this clinical trial is to learn if an artificial intelligence model will be able to select patients with advanced breast cancer who may respond to a second cyclin-dependent kinase 4/6 (CDK4/6) inhibitor after they…
- Trial name
- AIM-BRIGHT (NCT07227233)
- Testing
- A CDK4/6 inhibitor different from the first that the participant had received, plus fulvestrant., Treatment of physician's choice
- Where
- United States
- Volunteers
- 105 people
- Sponsor
- University of California, San Diego
Clinical Reasoning in Nursing Education, Virtual Simulation
MAGICS - Multi-Agent Generative AI in Clinical Simulation for Clinical Deterioration Training
This study compares the effectiveness of a Generative AI-integrated blended simulation programme and high-fidelity simulation alone on nursing students' clinical reasoning and learning experience during deterioration training
- Conditions
- Clinical Reasoning in Nursing Education, Virtual Simulation, Artificial Intelligence in Education, Deterioration, Clinical
- Trial name
- MAGICS (NCT07872735)
- Testing
- Generative AI-integrated Blended Simulation, High Fidelity Simulation
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- National University of Singapore