Digital Health Frontier
By John Halamka and Paul Cerrato - Software as a medical device continues to evolve with advances in machine learning. So do the federal regulations governing these digital tools.
By Paul Cerrato and John Halamka - One of the goals of our weekly blog is to explain, in plain English, how digital tools can improve patient care. This week we unravel convolutional neural networks and random forest analysis.
By John Halamka and Paul Cerrato - The evidence indicates it won’t solve this national epidemic but can serve as a valuable adjunct to professional therapy.
The agency’s draft guidelines cover a wide range of complex issues, including patients’ ability to handle remote monitoring devices and correctly record data, how to[...]
By John Halamka and Paul Cerrato- While many health care startups begin as daydreams in the minds of creative geniuses, entrepreneurs with the right blend of passion, observational skills, and imagination are the future of digital medicine.
By John Halamka and Paul Cerrato - In the second installment in the series, we explain how gradient boosting can help make patient care more precise and cost effective.
By John Halamka and Paul Cerrato - Many physicians ignore the recommendations provided by machine learning algorithms because they don’t trust them. A few imaginative software enhancements may give them more confidence in an algorithm’s diagnostic and therapeutic suggestions.
By John Halamka and Paul Cerrato - The potential benefits of AI-enabled algorithms have to be weighed against the risk of dataset shift, which can compromise their accuracy in ways that developers never anticipated.
By John Halamka and Paul Cerrato - Our vision for health care technology includes a steadfast determination to use AI to augment human intelligence — not contribute to a dystopian future some fear is already upon us.
By John Halamka and Paul Cerrato - One of the privileges we enjoy working in digital health is the opportunity to use state-of-the-art AI tools to unearth actionable insights from millions of patient records, without compromising their privacy.
By John Halamka and Paul Cerrato - Machine learning-enhanced algorithms may help clinicians select the best medications for each patient, speeding up the long journey to find effective relief for a crippling disorder.
By John Halamka and Paul Cerrato - Some clinicians reject any AI-infused recommendations, while others are so confident in these tools that they forfeit their independent diagnostic skills. A closer look at the research can turn these mistakes into insights.