JMIR Medical Education

ChatGPT has been tested in health care, including the US Medical Licensing Examination and specialty exams, showing near-passing results. Its performance in the field of anesthesiology has been assessed using English board examination questions; however, its effectiveness in Korea remains unexplored.

Australian nursing programs aim to introduce students to digital health requirements for practice. However, innovation in digital health is more dynamic than education providers’ ability to respond. It is uncertain whether what is taught and demonstrated in nursing programs meets the needs and expectations of clinicians regarding capability of nurse graduates.

The use of digital online teaching media in improving surgical skills of medical students is indispensable, yet it is still not widely explored objectively. The first-person-view online teaching method may be more effective as it provides more realism to surgical clerkship students in achieving basic surgical skills.

Healthcare delivery is undergoing an accelerated period of digital transformation, spurred in-part by the COVID-19 pandemic and the use of “virtual-first” care delivery models like telemedicine. Medical education has responded to this shift with calls for improved digital health training, but there is as yet no universal understanding of needed competencies, domains, and best practices for teaching these skills. In this paper, we argue that a “digital determinants of health” (DDoH) framework for understanding intersections of health outcomes, technology, and training is critical to the development of comprehensive digital health competencies in medical education. Much like current social determinants of health models, the DDoH framework can be integrated into undergraduate, graduate, and professional education to guide training interventions as well as competency development and evaluation. We provide possible approaches to integrating this framework into training programs and explore priorities for future research in digitally-competent medical education.

The rapidly aging population and the growth of geriatric medicine in the field of internal medicine are not supported by sufficient gerontological training in many health care disciplines. There is rising awareness about the education and training needed to adequately prepare health care professionals to address the needs of the older adult population. Massive open online courses (MOOCs) might be the best alternative method of learning delivery in this context. However, the diversity of MOOC participants poses a challenge for MOOC providers to innovate in developing learning content that suits the needs and characters of participants.

Text-generating Artificial Intelligence (AI) such as ChatGPT offers many opportunities and challenges in medical education. Acquiring the practical skills necessary for utilizing AI in a clinical context is crucial, especially during the education of medical students.

Clinical practice settings have increasingly become dependent on the use of digital or eHealth technologies such as electronic health records. It is vitally important to support nurses in adapting to digitalized health care systems; however, little is known about nursing graduates’ experiences as they transition to the workplace.

Although history taking is fundamental for diagnosing medical conditions, teaching and providing feedback on the skill can be challenging due to resource constraints. Virtual simulated patients and web-based chatbots have thus emerged as educational tools, with recent advancements in artificial intelligence (AI) such as large language models (LLMs) enhancing their realism and potential to provide feedback.

China's secondary vocational medical education is essential for training primary healthcare personnel and enhancing public health responses. This education system currently faces challenges, primarily due to its emphasis on knowledge acquisition which overshadows the development and application of skills, especially in the context of emerging Artificial Intelligence (AI) technologies. This article delves into the impact of AI on medical practices and uses this analysis to suggest reforms for the vocational medical education system in China. AI is found to significantly enhance diagnostic capabilities, therapeutic decision-making, and patient management. However, it also brings about concerns such as potential job losses and necessitates the adaptation of medical professionals to new technologies. Proposed reforms include a greater focus on critical thinking, hands-on experiences, skill development, medical ethics, and integrating humanities and AI into the curriculum. These reforms require ongoing evaluation and sustained research to effectively prepare medical students for future challenges in the field.

Official conference hashtags are commonly used to promote tweeting and social media engagement. The reach and impact of introducing a new hashtag during an oncology conference have yet to be studied. The American Society of Clinical Oncology (ASCO) conducts an annual global meeting, which was entirely virtual due to the COVID-19 pandemic in 2020 and 2021.

With the increasing application of Large Language Models (LLMs) like ChatGPT in various industries, its potential in the medical domain, especially in standardized examinations, has become a focal point of research.

ChatGPT was not intended for use in health care, but it has potential benefits that depend on end-user understanding and acceptability, which is where health care students become crucial. There is still a limited amount of research in this area.