JMIR Medical Education

Summary Sentence: Bing Chat (subsequently renamed Microsoft Copilot), a ChatGPT 4.0 based Large Language Model, demonstrated comparable performance to medical students in answering essay-style CAPPs, while assessors struggled to differentiate AI from human responses. These results highlight the need to prepare students and educators for a future world of AI by fostering reflective learning practices and critical thinking.

Although the training course of electrocardiogram (ECG) interpretation was started early in medical school, the accuracy in interpretation of 12-lead ECG is always a challenge issue. We conducted a pilot educational program to compare the effectiveness of a conventional didactic lecture, self-drawing (SD), and self-drawing following a flipped classroom approach (SDFC).

Doctor-to-Doctor (D2D) is a mobile learning app that aims to support continuous learning in health care, commonly known as continuing medical education. One of the metrics of success in mobile learning is the average amount of time spent each month on the app, which is a component of stickiness, the tendency of users to use apps repeatedly. Stickiness metrics are important because stickiness has a direct effect on user retention.

A virtual simulated placement (VSP) is a computer-based version of a practice placement. COVID-19 drove increased adoption of virtual technology in clinical education. Accordingly, the number of VSP publications increased from 2020. This review determines the scope of this literature to inform future research questions.

The traditional history and physical (H&P) provides the basis for physicians’ data gathering, problem formulation, and care planning, yet it can miss relevant behavioral or social risk factors. The American Medical Association’s “H&P 360,” a modified H&P, has been shown to foster information gathering and patient rapport in inpatient settings and objective structured clinical examinations. It prompts students to explore 7 domains, as appropriate to the clinical context: biomedical problems, psychosocial problems, patients’ priorities and goals, behavioral history, relationships, living environment and resources, and functional status.

Programmatic assessment supports flexible learning and individual progression, but challenges educators to develop frequent assessments reflecting different competencies. The continuous creation of large volumes of assessment items, in a consistent format, in a comparatively restricted time, is laborious. To address this challenge, the application of technological innovations, including artificial intelligence (AI), has been tried. A major concern raised is the validity of the information produced by AI tools, and if not properly verified, can produce inaccurate and therefore inappropriate assessments.

Understanding the roles and patient management approaches of the entire oncology team is imperative for effective communication and optimal cancer treatment. Currently, there is no standard residency or fellowship curriculum to ensure delivery of fundamental knowledge and skills associated with oncology specialties with which trainees often collaborate.

Artificial intelligence (AI) systems are becoming increasingly relevant in everyday clinical practice, with FDA-approved AI solutions now available in many specialties. This development has far-reaching implications for doctors and the future medical profession, highlighting the need for both practicing physicians and medical students to acquire the knowledge, skills, and attitudes necessary to effectively use and evaluate these technologies. Currently, however, there is limited experience with AI-focused curricular training and continuing education.

Alzheimer’s disease (AD) presents significant challenges to healthcare systems worldwide. Early and accurate diagnosis of AD is crucial for effective management and care to enable timely treatment interventions that can preserve cognitive function and improve patient quality of life. However, there are often significant delays in diagnosis. Continuing medical education (CME) has enhanced physician knowledge and confidence in various medical fields, including AD. Notably, web-based CME has been shown to positively influence physician confidence, which can lead to changes in practice and increased adoption of evidence-based treatment selection.

Standardized patients (SPs) have been crucial in medical education, offering realistic patient interactions to students. Despite their benefits, SP training is resource-intensive, and access can be limited. Advances in artificial intelligence, particularly with large language models like ChatGPT, present new opportunities for virtual SPs, potentially addressing these limitations.

Medical students face high levels of burnout and mental health issues during training. Understanding associated factors can inform supportive interventions.

Telemedicine is a key element of modern healthcare, providing remote medical consultations and bridging the gap between patients and healthcare providers. Despite legislative advancements and pilot programs, the integration of telemedicine education in Romania remains limited. Addressing these educational gaps is essential for preparing current and future medical professionals to effectively use telemedicine technologies.