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Featured
Can Patients Trust Chatbots to Manage and Interpret Their Medical Data?
By John Halamka and Paul Cerrato — Chatbots are offering a quick way for patients to collect and access their records, but the tools they are using are not always secure, or accurate.
By John Halamka and Paul Cerrato — Mayo Clinic’s Tapestry Study has demonstrated that next generation genetic analysis can have a significant impact on patient care.
Against the backdrop of the 43rd Annual J.P. Morgan Healthcare Conference, Mayo Clinic announced the formation of Mayo Clinic Digital Pathology, designed on a platform architecture to boldly unlock the power of its extensive archive of digital slides to revolutionize pathology and accelerate medical breakthroughs.
By John Halamka and Paul Cerrato — Imagine if you could create a digital clone of yourself that can be used to test various treatment options to determine which one is best for your real self.
By John Halamka and Paul Cerrato — Data scientists use a variety of coding languages to create AI-driven models, but the real “secret sauce” that helps them identify the best algorithms are the weights the coding generates.
By John Halamka and Paul Cerrato — Several of these digital tools are supported by strong evidence and are worth considering, not to replace your clinical judgement, but to augment it.
By John Halamka and Paul Cerrato — All the good things in the world worth believing, and among those good things are the therapeutic power of kindness and the healing effects of music.
By John Halamka, Paul Cerrato, and Sonya Makhni — How do you construct a safe, effective algorithm? It’s not an easy question to answer, but with a well thought out roadmap, it’s doable.
Mayo Clinic Platform_Accelerate has announced a strategic agreement with the Japan External Trade Organization (JETRO) to implement a two-phase program aimed at enhancing U.S. healthcare and business immersion opportunities for Japanese health technology companies.
By John Halamka and Paul Cerrato — Even the most accurate algorithm is useless if it can’t be seamlessly implemented into a hospital’s workflow. Here’s a way to make that happen.
By John Halamka, Paul Cerrato, and Teresa Atkinson — Many clinicians are well aware of the shortcomings of LLMs, but studies suggest that retrieval-augmented generation could help address these problems.
By John Halamka and Paul Cerrato — Large language models rely on complex technology, but a plain English tutorial makes it clear that they use math, not magic to render their impressive results.
By John Halamka and Paul Cerrato — Many algorithms only reinforce a person’s narrow point of view, or encourage existing prejudices. There are better alternatives.