Digital Health Frontier
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[...]
By John Halamka and Paul Cerrato—NLP enables humans and computers to communicate in ways never imagined a few short years ago. The results have practical implications for anyone working in healthcare.
By John Halamka and Paul Cerrato— Guidelines and guardrails for the safe use of AI require more than regulation. The Coalition for Health AI has created a framework to reduce these risks and improve the safety and effectiveness of these models.
By John Halamka and Paul Cerrato — The capabilities of generative AI continue to grow. Using them wisely will likely improve clinical decision making.
By John Halamka and Paul Cerrato — The Oxford Dictionary says disease is a disorder of structure or function, especially one that has a known cause and a distinctive group of symptoms, signs, or anatomical changes. It’s time to rethink that simplistic definition.
By John Halamka and Paul Cerrato — In part one, we discussed the shortcomings of evidence-based medicine and the disconnect between RCTs and bedside clinical care. Part 2 explores possible solutions, including machine learning-based algorithms.
By John Halamka and Paul Cerrato — Evidence-based medicine has benefited patients in countless ways, but there’s a disconnect between EBM and the clinical care that is typically delivered at the bedside. Pragmatic, real-world trials and AI-based algorithms may help solve the problem.