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:
o Look for teams that have deep expertise in both the technology and the domain.
o 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:
o Early detection
o Timely improvement in outcomes
o Reduction in diagnostic errors
o Time savings for clinicians
o Overall reduction in healthcare waste