Clinical trials: Artificial Intelligence in Education
Scoliosis Patients
Artificial Intelligence and Scoliosis
The aim of the study to use artificial intelligence technology in assessment of scoliosis degree of severity and to personalize for treatment plan for each pa tient .
- Trial name
- NCT06589583
- Where
- Egypt
- Volunteers
- 5,000 people, healthy volunteers welcome
- Sponsor
- Delta University for Science and Technology
Periodontal Diseases
Deep Learning-Based Measurement of Keratinized Gingiva Width Using Smartphone-Acquired Clinical Images
This study aims to develop and validate an artificial intelligence-based system for automated measurement of keratinized gingiva width using smartphone-acquired intraoral clinical photographs.
- Trial name
- NCT07689552
- Testing
- Artificial Intelligence-Based Keratinized Gingiva Width Assessment
- Where
- Egypt
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- Al-Azhar University
COVID-19, COVID
COVID-19 Infection and Machine Learning Using Artificial Intelligence (AI)
COVID-19 infection is currently confirmed by a complex, multiple-step procedure starting with a mucosal swab, followed by viral RNA extraction and processing and qPCR.
- Conditions
- COVID-19, COVID, SARS-CoV 2
- Trial name
- NCT04756518
- Where
- United Kingdom
- Volunteers
- 215 people
- Sponsor
- East Suffolk and North Essex NHS Foundation Trust
Dyspnea
Artificial Intelligence to Improve Physicians' Interpretation of Chest X-Rays in Breathless Patients
Identifying the cause of breathlessness in acute patients in the emergency department is critical and challenging. The chest X-ray is central but challenging to read for non-radiologist physicians.
- Trial name
- XRAI (NCT05117320)
- Testing
- AI support
- Where
- Denmark
- Volunteers
- 33 people, healthy volunteers welcome
- Sponsor
- Bispebjerg Hospital
Gingival Phenotype Assessment
Comparison of Artificial Intelligence and Clinicians With Different Experience Levels in Assessing Gingival Phenotype
The goal of this observational study is to compare the performance of clinicians with different experience levels and a deep learning-based artificial intelligence (AI) model in assessing gingival phenotype using two diagnostic…
- Trial name
- NCT07570290
- Testing
- Periodontal Probe Transparency Method, Visual Assessment Method, Deep Learning-Based Artificial Intelligence Model
- Volunteers
- 40 people, healthy volunteers welcome
- Sponsor
- Ondokuz Mayıs University
Osteogenesis Imperfecta, Rare Bone Disorders
Morphology in Oral Rare Syndromes & Artificial Intelligence for Clinical Diagnosis
MOSAIC aims to determine whether oro-dental morphological anomalies, particularly palatal morphology, associated with rare bone and cartilage diseases can be precisely characterized using 3D digital models analysed through…
- Conditions
- Osteogenesis Imperfecta, Rare Bone Disorders, Hypophosphatemia, X-Linked
- Trial name
- MOSAIC (NCT07666269)
- Testing
- intra-oral 3D optical impression
- Where
- France
- Volunteers
- 240 people, healthy volunteers welcome
- Sponsor
- University Hospital, Bordeaux
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
PTSD - Post Traumatic Stress Disorder, Trauma-related Nightmares
Validation of an Algorithm for Predicting Awakenings Associated With Trauma-related Nightmares, Based on the Analysis of Physiological Patterns in Military and Former Military Patients Suffering From Post-traumatic Stress Disorder
The goal of this clinical trial is to validate an artificial intelligence algorithm called CAUD-PIN (CAUchemar Detection on INdividualized Parameters) to predict nightmare-related awakenings in military personnel and veterans…
- Trial name
- CAUD-PIN (NCT07851480)
- Testing
- CAUD-PIN (CAUchemar Detection on INdividualized Parameters) - AI-based predictive algorithm forTrauma-related nightmare awakenings
- Where
- 3 sites in France
- Volunteers
- 27 people
- Sponsor
- Direction Centrale du Service de Santé des Armées
Lung Cancer (Diagnosis)
AI-Personalized Discharge Education for Patients After Lung Cancer Surgery
This randomized controlled trial evaluates the effect of artificial intelligence (AI)-personalized discharge education on discharge teaching quality and recovery outcomes in patients after lung cancer surgery.
- Trial name
- AI-LUNG (NCT07827183)
- Testing
- AI-Personalized Discharge Education, Routine Discharge Education
- Where
- China
- Volunteers
- 156 people
- Sponsor
- Xiamen University
Nursing Education, Simulation-Based Learning
Effects of Concept Mapping and AI Dialogue on Flow and Learning Outcomes in Simulation-Based Learning
This mixed-methods educational study evaluates the integration of concept mapping and artificial intelligence (AI)-supported dialogue into simulation-based learning for nursing students.
- Trial name
- NCT07748897
- Testing
- ChatGPT-Assisted Preparation for Pediatric Nursing Simulation, Standard Preparation for Pediatric Nursing Simulation
- Where
- Taiwan
- Volunteers
- 168 people, healthy volunteers welcome
- Sponsor
- Chang Gung University of Science and Technology
Locally Advanced Rectal Cancer (LARC)
AI-Based Prediction of Pathological Response in Rectal Cancer Patients Receiving Total Neoadjuvant Therapy
This study aims to better understand how body composition, inflammation, and nutrition affect how rectal cancer responds to treatment.
- Trial name
- CINR-AI (NCT07049627)
- Testing
- Total Neoadjuvant Therapy (TNT)
- Where
- 2 sites in Turkey (Türkiye)
- Volunteers
- 93 people
- Sponsor
- Ankara Etlik City Hospital
Parkinson Disease, Occupational Therapy Students
Effect of AI Chatbot-Assisted Versus Traditional Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Study on Parkinson's Disease
This study aims to examine whether using an artificial intelligence (AI) chatbot can enhance occupational therapy students' learning during a case-based activity focused on Parkinson's disease.
- Conditions
- Parkinson Disease, Occupational Therapy Students, Clinical Reasoning, Neurologic Rehabilitation
- Trial name
- AI-PD-OT25 (NCT07045077)
- Testing
- AI Chatbot-Assisted Case-Based Learning, Traditional Case-Based Learning with Standard Materials
- Where
- Turkey (Türkiye)
- Volunteers
- 25 people, healthy volunteers welcome
- Sponsor
- Ceyhun Türkmen
Breast Cancer, Anxiety
The Impact of AI- Supported Education in Mastectomy Patient
This study aims to evaluate the impact of artificial intelligence (AI)-supported preoperative education on fear and anxiety levels in patients undergoing total mastectomy.
- Conditions
- Breast Cancer, Anxiety, Mastectomy, Patient Education as Topic
- Trial name
- AI-ME (NCT06796166)
- Testing
- AI-Supported Preoperative Education, Standard Preoperative Education
- Where
- Turkey (Türkiye)
- Volunteers
- 40 people
- Sponsor
- Bezmialem Vakif University
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
Murmur, Heart, Innocent Murmurs
Real-World Evaluation of Eko Algorithms in a Point of Care Setting
The purpose of this research is to prospectively test and validate the utility of Eko artificial intelligence (AI) plus Eko Murmur Analysis Software (EMAS) murmur characterization in algorithm in a real world, point-of-care…
- Conditions
- Murmur, Heart, Innocent Murmurs, Heart Murmurs, Pathologic Murmur
- Trial name
- NCT05459545
- Testing
- Use of Eko CORE and Eko CORE 500 electronic stethoscope
- Where
- 5 sites in United States
- Volunteers
- 371 people, healthy volunteers welcome
- Sponsor
- Eko Devices, Inc.
Artificial Intelligence, Machine Learning
Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning
The goal of this clinical trial is to study whether the use of our blood culture prediction tool is non-inferior to current practice and if it can improve certain outcomes in all adult patients presenting to the emergency…
- Conditions
- Artificial Intelligence, Machine Learning, Microbiology, Emergency Service, Hospital
- Trial name
- ABC (NCT06163781)
- Testing
- Blood culture prediction tool
- Where
- Netherlands
- Volunteers
- 7,584 people, healthy volunteers welcome
- Sponsor
- Amsterdam UMC, location VUmc
To Evaluate the Added Value of the Use of Artificial Intelligence in the Diagnosis of Referable Diabetic Retinopathy in a Teaching Hospital Setting
Performance Evaluation of Artificial Intelligence Assisted Diabetic Retinopathy Grading in the Leuven University Hospital: Can Technology Improve the Resident?
To evaluate the added value of the use of artificial intelligence in the diagnosis of referable diabetic retinopathy in a teaching hospital setting
- Trial name
- PEARL (NCT05260281)
- Testing
- MONA algorithm
- Volunteers
- 139 people
- Sponsor
- Universitaire Ziekenhuizen KU Leuven
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
Nursing Process Competence, Artificial Intelligence Perception and Attitude
The Effect of AI-Assisted Nursing Process Training on Nursing Process Competence, Perception and Attitudes Towards Artificial Intelligence in Nurses: A Randomized Controlled Study
This study aims to determine how applied artificial intelligence (AI) training affects nurses' ability to manage the nursing process and their perceptions and attitudes toward AI technology The nursing process is a scientific…
- Conditions
- Nursing Process Competence, Artificial Intelligence Perception and Attitude, Nursing Education, Nursing Process
- Trial name
- NCT07618975
- Testing
- Artificial Intelligence-Supported Nursing Process Training, Standard Theoretical Education on the Nursing Process
- Where
- Turkey (Türkiye)
- Volunteers
- 78 people, healthy volunteers welcome
- Sponsor
- University of Yalova
Embolic Stroke of Undetermined Source
AI-Based Prediction of Atrial Fibrillation in ESUS Patients With ICM
This study investigates patients with Embolic Stroke of Undetermined Source (ESUS) who have received an Implantable Cardiac Monitor (ICM).
- Trial name
- SMART-ESUS (NCT07347691)
- Where
- 5 sites in South Korea
- Volunteers
- 92 people
- Sponsor
- Inha University Hospital