Medical education assessment faces multifaceted challenges, including data complexity,
resource constraints, bias, feedback translation, and educational continuity. Traditional …

The proliferation of generative artificial intelligence (AI) and its extensive potential for
integration into many aspects of health care signal a transformational shift within the health …

Competency-based medical education (CBME) is an outcomes-based approach to
education and assessment that focuses on what competencies trainees need to learn in …

The goal of medical education is to produce a physician workforce capable of delivering
high-quality equitable care to diverse patient populations and communities. To achieve this …

A central goal of precision education (PE) is efficiently delivering the right educational
intervention to the right learner at the right time. This can be achieved through a PE cycle …

ChatGPT (OpenAI), a cutting-edge natural language processing model, holds immense
promise for revolutionizing medical education. With its remarkable performance in language …

High-quality precision education (PE) aims to enhance outcomes for learners and society by
incorporating longitudinal data and analytics to shape personalized learning strategies …

Precision education (PE) uses personalized educational interventions to empower trainees
and improve learning outcomes. While PE has the potential to represent a paradigm shift in …

Precision education (PE) leverages longitudinal data and analytics to tailor educational
interventions to improve patient, learner, and system-level outcomes. At present, few …

Purpose The era of precision education is increasingly leveraging electronic health record
(EHR) data to enhance precision in our assessments of residents' clinical performance. But …