By John Halamka and Paul Cerrato - The broad access to such services that occurred at the beginning of the COVID-19 pandemic should not be rolled back. Finding a way to extend the regulatory waivers that made this possible is in our patients’ best interest.

With the recent launch of a product to evaluate artificial intelligence (AI) models for accuracy and susceptibility to bias, Mayo Clinic Platform is accelerating adoption of data-driven innovation in clinical practice.

By John Halamka and Paul Cerrato - There’s no shortage of startups with creative ways to use the technology to improve patient care and make clinicians’ lives less burdensome, and that includes digital assistants.

By John Halamka and Paul Cerrato - EHR optimization remains an elusive goal for many health care providers, but several digital assistants may help solve the problem.

As health systems and insurance companies ramp up adoption of artificial intelligence and machine learning technology, experts fear clinical algorithms are not ready for prime time—with potential consequences for patient safety and outcomes.

By John Halamka and Paul Cerrato - Enabled by natural language processing, these digital tools are slowly finding their way into clinical practice. Despite the potential to make it easier to navigate an EHR system, they come with problems of their own.

The research is mounting to show that Anumana’s AI-ECG algorithms could dramatically improve screening for cardiovascular disease (CVD), providing early warnings of disease from just a standard electrocardiogram (ECG).

By John Halamka and Paul Cerrato - We can empower patients by providing high quality educational materials, encouraging medical self-care, and by finding ways to incorporate patient-generated health data into clinical practice.

By John Halamka and Paul Cerrato -Three patient populations are underrepresented in the AI models currently being developed. There are several practical solutions to the problem.