Prashant Natarajan is the Vice President of Strategy & Products at H2O.ai. He is a best-selling author and co-author of books on healthcare & life sciences who focuses on demystifying complex technology topics, strategy, and digital transformation programs.
The latest book he is a co-author of is, Demystifying AI for the Enterprise- a Playbook for Business Outcomes & Digital Transformation (2021).
Summary
In this episode, Prashant takes us on a Data trip. He introduces us to Data Fidelity and explains the various attributes of data that may be relevant in a healthcare setting. He gives us a blueprint of how a healthcare enterprise may start planning their journey towards AI adoption.
Audience Questions
[00:36:45]What are some of the toughest problems in the health services sector that seem outside the reach of current AI? Further, is this the case because of a lack of data or other moving parts?
Sanju Menon – Data Scientist @ UBS
[00:41:57] How will common people understand the use of AI in Healthcare that will empower them to ask relevant and important questions to their HCP regarding the care being given?
Sravani Marpaka — Senior Pharmacovigilance Associate
Topical Questions
[00:04:32] Since we’re talking about health care in this podcast, could you sort of talk about what data fidelity is and definitely what is data fidelity in the context of healthcare?
[00:10:35] How do you understand data in a healthcare setting? In what dimensions, how much of data is enough? And you also talked about something called social determinants of health. How does that fit into this data that I mentioned for patients?
[00:20:22] If you were to guide a healthcare client or healthcare enterprise in their steps into the AI journey or of deriving insights from their data and using AI and ML to drive better outcomes, whatever they may be to find, how would you sort of coach them and guide them? How would you get them started? What would be your blueprint for them?
Quotable Quotes
[00:07:38] Data Fidelity…I defined it as the quality of data in the context of its use and in the context of its user.
[00:18:10] I think it’s high time for the industry to not just look at data within the four walls of the health system or at home, but start looking at healthcare data as a representative of the datafication that is happening in general.
[00:24:05] I define explainability as taking the results of interpretability and being able to explain that to an audience that is not a data scientist, that is not a data engineer, that is not somebody who has a degree in biostatistics or computational biology or medicine.
[00:40:13] People who claim that AI, ML can replace physicians know nothing about medicine and know nothing about AI.
[00:41:07] Healthcare AI is going to create happier clinicians, happier leaders, most importantly, happier patients and it’s going to remove the mundane and increase the sublime.
[00:46:50] Go forth bravely with confidence in technology, in the importance of healthcare, AI for public health, population health and precision medicine and let’s build a community together that will improve health and wellness globally.
Notable Mentions
[00:31:15] Florence Nightingale
[00:20:57] Demystifying Big Data and ML for Healthcare
[00:34:54] Demystifying AI for the Enterprise
[00:02:31] The You+AI Podcast is among the Top 8 healthtech podcasts globally
Pointers to past You+AI Podcast episodes
[00:32:37] S1-E1 The Doctor Patient Relationship, with Dr. T. R. Gopalan
Connect
LinkedIn: Prashant Natarajan
Twitter: @natarpr
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