Digital Health Frontier
By John Halamka and Paul Cerrato — Machine learning-based algorithms can now be used to help detect atrial fibrillation, asymptomatic left ventricular systolic dysfunction, and cardiac amyloidosis. Even more digital diagnostic tools are on the drawing board.
By John Halamka and Paul Cerrato — Questioning the status quo and challenging conventional wisdom can result in innovative solutions to once intractable problems, but we must avoid reflexive contrarianism.
By John Halamka and Paul Cerrato — Large language models like ChatGPT have the potential to profoundly benefit and seriously harm patients. With that in mind, it makes sense to understand the underlying technology.
By John Halamka and Paul Cerrato — With so much hyperbole in the news, it’s difficult to separate false promises from genuine medical breakthroughs. Advances in genomics fall into the latter category.
By John Halamka and Paul Cerrato — The Coalition for Health AI was created to help end users separate trustworthy, useful technology from technology that only seems to move us in the right direction.
By John Halamka and Paul Cerrato — Coloring outside the lines has always been a challenge for healthcare providers. There are several ways to address the problem.
By John Halamka and Paul Cerrato — Modern healthcare could not survive without experts and their years of experience and training, but when expertise becomes dogmatic, innovation is slowed. We need to be more inclusive in our definition of expertise.
By John Halamka and Paul Cerrato — Mayo Clinic Platform_Connect is transforming how patient data is used to generate innovative diagnostic tools and treatment options.
By John Halamka and Paul Cerrato — What happens when ChatGPT-4 and a human cardiologist are asked to diagnose the same patient? The results are quite revealing.
By John Halamka and Paul Cerrato — Several thought leaders and stakeholders have joined forces to create GoodDx.org, a searchable database that has the potential to reduce the human suffering affecting millions of Americans.
By John Halamka and Paul Cerrato — The agency recently posted new recommendations for AI developers who want to update their software as a medical device (SAMD). The document offers what we hope will be a less burdensome way to manage the Predetermined Change Control Plan.
Guest post by Sonya Makhni — Understanding their limitations, defining the best use cases, and closing the gaps in transparency and trustworthiness are the keys to responsible LLM adoption.