Podcast: AI, Big Data and Existing Challenges (Part Two)

Samara Rosenfeld
FEBRUARY 04, 2020


Artificial intelligence (AI)-based clinical diagnostic tools have the potential to not only improve outcomes but increase workflow efficiency. Many physicians want the opportunity to use potentially game-changing technologies, but challenges still exist.

In part two of our two-part podcast, Paul Cerrato, former editor of InformationWeek Healthcare, discussed the criticisms, obstacles and limitations of new diagnostic and therapeutic tools, whether big data analytics can improve existing clinical decision support systems and if AI-based tools will ultimately replace human diagnostic reasoning.

Cerrato has more than 30 years of experience working as a research analyst, medical journalist, clinician, and educator and has written extensively on clinical decision support, electronic health records, protected health information security and practice management. For listeners attending HIMSS 2020 in Orlando, Florida, Cerrato and Halamka will be leading a preconference session “Reinventing Clinical Decision Support” on Monday, March 9 from 1:30–2:10 p.m. and an educational session “Reinventing Clinical Decision Support With Machine Learning” on Tuesday, March 10 from 12–1 p.m.

Before listening to this episode, check out part one, where Cerrato spoke about his latest book, the cause of diagnostic errors and how machine learning can improve patient outcomes.

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How Clinical Decision Support Tools Can Improve Outcomes (Part One)
Health Tech in the 2010s and Beyond
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