The Lancet Digital Health

Artificial Intelligence (AI) has the potential to better train doctors via personalising learning experiences, simulating clinical scenarios and supporting research. Yet, there are human, financial and resource-based barriers to its adoption. Healthcare institutions, medical schools, industry partners and government bodies need to work together to develop responsible and effective solutions.

An international consortium led by Duke-NUS Medical School introduces an ethics checklist for systematic and standardised assessment for research involving generative AI technologies in healthcare settings, enhancing accountability

Potential benefits of method include subjecting patients to fewer exams and reducing health care costs

Osaka Metropolitan University scientists have successfully developed a model that utilizes AI to accurately classify cardiac functions and valvular heart diseases from chest radiographs. The Area Under the Curve, or AUC, of the AI classification showed a high level of accuracy, exceeding 0.85 for almost all indicators and reaching 0.92 for detecting left ventricular ejection fraction—an important measure for monitoring cardiac function.