Large language models (LLMs) have demonstrated impressive capabilities, but the bar for
clinical applications is high. Attempts to assess the clinical knowledge of models typically rely …

Self-supervised pretraining followed by supervised fine-tuning has seen success in image
recognition, especially when labeled examples are scarce, but has received limited attention …

Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases
are seen instead by general practitioners with lower diagnostic accuracy. We present a …

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing patient …

Large language models (LLMs) have demonstrated impressive capabilities in natural language
understanding and generation, but the quality bar for medical and clinical applications is …

Machine learning (ML) systems often exhibit unexpectedly poor behavior when they are
deployed in real-world domains. We identify underspecification in ML pipelines as a key reason …

This paper complements a recent study by Ramos‐Rodriguez and Ruiz‐Navarro (2004)
that investigated the intellectual structure of the strategic management field through co‐citation …

Studies have shown that a dominant class of questions asked by visually impaired users on
images of their surroundings involves reading text in the image. But today's VQA models can …

Recent artificial intelligence (AI) systems have reached milestones in "grand challenges"
ranging from Go to protein-folding. The capability to retrieve medical knowledge, reason over it, …

Synchronverters are inverters that mimic the behavior of synchronous generators. In this
paper, we propose five modifications to the synchronverter algorithm from the paper “…