Radin et al.’s recent study on patients with long COVID demonstrates that personal wearable data can provide critical insight into complex conditions. This editorial argues that research insights gained through personal wearables support the integration of personal wearables into healthcare. Challenges in incorporating wearable data in the clinic point towards AI data sorting, data sharing, device

Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers

India’s evolving digital health strategy leverages innovative technologies to enhance access to healthcare services. This paper explores the key components of India’s digital health transformation, including the Ayushman Bharat Digital Mission (ABDM) and India’s integration of biometric identification and digital infrastructure to improve healthcare delivery. The lessons learned from India’s large-scale

Artificial Intelligence (AI) systems are increasingly being deployed across various high-risk applications, especially in healthcare. Despite significant attention to evaluating these systems, post-deployment incidents are not uncommon, and effective mitigation strategies remain challenging. Drug safety has a well-established history of assessing, monitoring, understanding, and preventing adverse effects

Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in