Digital Health Frontier
By John Halamka and Paul Cerrato — It may sound counterintuitive, but the evidence indicates slowing down can help.
By John Halamka and Paul Cerrato— AI-based algorithms have a place in the emergency department, but clinicians still need to separate signal from noise.
By John Halamka and Paul Cerrato — Many hospitals are purchasing the latest AI algorithms to streamline operations and improve clinical care. But few of these models are being fully vetted for accuracy, bias, and transparency.
By John Halamka and Paul Cerrato — Healthcare professionals rely heavily on their clinical experience, supplemented by what they read in the medical literature. Several developers are trying to add AI algorithms into the mix.
By John Halamka and Paul Cerrato — Are chatbots making clinicians lazy, or convincing us to place too much confidence in their diagnostic prowess?
By John Halamka and Paul Cerrato — There are many environmental factors that influence our risk of disease, and so many interactions among these factors. The right AI tools can help untangle the knots.
By John Halamka and Paul Cerrato — Generative AI has the potential to transform patient care, but it can also wreak havoc if left unattended.
By John Halamka and Paul Cerrato — Since ChatGPT was launched in 2022, the entire world has suddenly taken notice of AI’s capabilities. AI agents use such large language models to actively reshape business, finance, and the healthcare ecosystem. Are we ready for this shift?
By John Halamka and Paul Cerrato—AI permeates our everyday lives in countless ways. It only makes sense for it to also improve the way medical school students are trained, and how clinicians in practice carry out their everyday responsibilities.
By John Halamka and John Cerrato—Our primer will give you many of the cognitive skills needed to understand the latest research on digital health.
By John Halamka and Paul Cerrato—Large language models like ChatGPT are finding their way into healthcare, business, and everyday life. The study of mechanistic interpretability may help us create safer, more trustworthy algorithms by “looking under the hood.”
These digital tools have the potential to transform patient care by tapping data resources rarely used in routine medical practice. By John Halamka, M.D., Diercks[...]