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Ep.116 State of play of AI/ML in healthcare. A discussion with Dr. Suchi Saria.

Inspiring Women with Laurie McGraw

Ep.116 State of play of AI/ML in healthcare. A discussion with Dr. Suchi Saria.

Laurie McGraw is speaking with Inspiring Woman Dr. Suchi Saria, Founder and CEO of Bayesian Health and prominent AI/ML healthcare expert.  With the tremendous excitement surrounding AI/ML, Suchi describes how to look behind…
March 15, 2023

Ep.116 State of play of AI/ML in healthcare. A discussion with Dr. Suchi Saria.

Laurie McGraw is speaking with Inspiring Woman Dr. Suchi Saria, Founder and CEO of Bayesian Health and prominent AI/ML healthcare expert.  With the tremendous excitement surrounding AI/ML, Suchi describes how to look behind the curtain to separate real solutions from just marketing.  Her road to healthcare came after years of solving hard complex problems.  After proving she could do hard, she wanted to move to something important and very impactful.  Healthcare is it.  With AI/ML, in just a few years she believes we should see measurable clinical impact in time to diagnose and treat, fewer diagnostic errors, more time back to clinicians all of which will remove a lot of waste in healthcare.

As Suchi continues to break new ground in healthcare, let’s all hope that she is right.

Hear Suchi talk about:

🧐    Why Bayesian Health?

  • Smart humans make decisions based on new incoming data and historical knowledge.
  • In healthcare, with vast data available in just the last several years, Bayesian aims to operationalize that decision making by surfacing data in an easy and usable way to augment clinicians who are doing more with less, treating sicker patients, and often feeling burnt out.

💉    State of play of AI/ML in healthcare:

  • Digital tools adoption and ChatGPT has led to a lot of excitement but also hype.
  • Behind the curtain (and the marketing) of AI/ML solutions:
    • Look for teams that have deep expertise in both the technology and the domain.
    • Expect reproducible results – clinically validated; financially validated; and stakeholder approved.
  • This is really hard. Progress will not happen overnight. But the opportunity is real.  This means putting one foot in front of the other every day.

🧭   Finding her compass – healthcare:

  • Meant moving from doing what was very hard to doing what was very important and meaningful.
  • It’s personal. Losing her nephew to sepsis fueled the urgency and her focus “to solve this”.

🗽  Professional growth and where she spends her time:

  • Every moment of growth has come from a moment of crisis.
  • She may have a brutal schedule, but work is play and play is work. Early mornings start with just thinking and often end watching comedy.  Living in NYC, every day can be an adventure.

🚀 Future opportunity with AI/ML in healthcare:

  • Expect an explosion of diagnostic software tools that can aid clinicians in real time with patient specific risk assessments.
  • Expect to see measurable clinical impact in the areas of:
    • Early detection
    • Timely improvement in outcomes
    • Reduction in diagnostic errors
    • Time savings for clinicians
    • Overall reduction in healthcare waste

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BIO

Suchi Saria is the Founder and CEO of Bayesian Health, the John C. Malone Associate Professor of computer science, statistics, and health policy, and the Director of the Machine Learning and Healthcare Lab at Johns Hopkins University. She has published over 50 peer-reviewed articles with over 3000 citations and was recently described as “the future of 21st century medicine” by The Sloan Foundation. Her research has pioneered the development of next-generation diagnostic and treatment planning tools that use statistical machine learning methods to individualize care.

At Bayesian Health, Dr. Saria is leading the charge to unleash the full power of data to improve healthcare, unburdening caregivers and empowering them to save lives. Backed by 21 patents and peer-reviewed publications in leading technical and clinical journals, Bayesian leverages best-in-class machine learning and behavior change management expertise to help health organizations unlock improved patient care outcomes at scale by providing real-time precise, patient-specific, and actionable insights in the EMR.

Dr. Saria’s work has received recognition in numerous forms including best paper awards at machine learning, informatics, and medical venues, a Rambus Fellowship (2004-2010), an NSF Computing Innovation Fellowship (2011), selection by IEEE Intelligent Systems to Artificial Intelligence’s “10 to Watch” (2015), the DARPA Young Faculty Award (2016), MIT Technology Review’s ‘35 Innovators under 35’ (2017), the prestigious Sloan Research Fellowship (2018), and the World Economic Forum Young Global Leader (2018). In sepsis, a life-threatening condition, her work first demonstrated the use of machine learning to integrate diverse signals to make early detection possible (Science Trans. Med. 2015). In Parkinson’s, her work showed a first demonstration of using readily-available sensors to easily track and measure symptom severity at home, which can serve to optimize treatment management (JAMA Neurology 2018).

Dr. Saria has traveled worldwide to conduct lectures and keynotes and most recently was an invited speaker at TEDMED 2020. In the past, she has given invited keynotes at several prestigious meetings including at The Royal Society, TEDxBoston,  the International Conference in Health Policy and Statistics (ICHPS), the National Academy of Medicine (NAM) Annual Meeting, the Montreal AI Symposium, the Uncertainty in Artificial Intelligence (UAI) meeting, the International Conference on Machine Learning (ICML), International Conference on Learning Representations (ICLR), and the Oxford Statistics Distinguished Seminar Series, to name a few.

Dr. Saria earned her M.Sc. and Ph.D. from Stanford University working with Professor Daphne Koller. She visited Harvard University as an NSF Computing Innovation Fellow and joined the Johns Hopkins faculty in 2012. Currently, Dr. Saria is serving as an advisor to the FDA on AI/machine learning.

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