Clinical Research Directory

Artificial Intelligence as a Decision Making Tool in Emergency Department

This study will evaluate the performance of a large language model (LLM)-based clinical decision support system in the emergency department at Rambam Health Care Campus. The system analyzes structured patient data from the electronic health record and generates diagnostic and treatment recommendations for physicians. The study will assess the system's ability to support diagnostic reasoning, its impact on diagnostic accuracy when used by physicians, and its perceived clinical usefulness. In addition, a retrospective analysis of de-identified patient records will be conducted to compare LLM-generated recommendations with actual clinical outcomes, including diagnosis, disposition decisions, and length of stay. The study will also examine the performance of the system in a multilingual clinical environment where both Hebrew and English are used in medical documentation and communication.

An AI Educational Agent for Medical Machine Learning Courses

The goal of this interventional study is to evaluate the effectiveness of a Large Language Model (LLM)-based educational AI Agent in graduate students (Masters and PhD) specializing in medicine or nursing who are enrolled in the "Machine Learning and Data Mining" course. The main questions it aims to answer are: Does the use of an educational AI Agent improve students' academic performance and practical skills in machine learning compared to traditional methods? Does the AI intervention enhance students' learning confidence, satisfaction, and cognitive engagement? Researchers will compare students currently using the AI Agent (experimental group) to a historical control group (students from the previous cohort who did not use the AI tool) to see if the AI-assisted learning model leads to significantly higher learning achievements and better educational experiences. Participants will: Utilize the Teaching Agent for real-time answers to theoretical questions, personalized study planning, and knowledge reinforcement. Engage with the Research Agent to assist with literature reviews, research design optimization, and academic writing structure. Use the Practice Innovation Agent for guidance on coding, algorithm debugging, and applying machine learning models to medical data analysis projects.