Qiao et al. recently investigated the ability of dual-energy X-ray absorptiometry (DXA) scans and a smartphone app to provide detailed body composition and shape data. In a healthcare system that continues to rely on crude and stigmatizing measurements like body-mass index (BMI), their findings point to the potential of newer technologies to capture markers (i.e., visceral adiposity and fat distribution

Current regulatory frameworks for artificial intelligence-based clinical decision support (AICDS) are insufficient to ensure safety, effectiveness, and equity at the bedside. The oversight of clinical laboratory testing, which requires federal- and hospital-level involvement, offers many instructive lessons for how to balance safety and innovation and warnings regarding the fragility of this balance

The Biden 2023 Artificial Intelligence (AI) Executive Order calls for the creation of a patient safety program. Patient safety reports are a natural starting point for identifying issues. We examined the feasibility of this approach by analyzing reports associated with AI/Machine Learning (ML)-enabled medical devices. Of the 429 reports reviewed, 108 (25.2%) were potentially AI/ML related, with 148

The introduction of the electronic health record was heralded as a technology solution to improve care quality and efficiency, but these tools have contributed to increased administrative burden and burnout for clinicians. Today, artificial intelligence is receiving much of the same attention and promises as electronic health records. Can healthcare learn from the failures of electronic health records

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