Today’s guest is Madhu Reddiboina, CEO of RediMinds Inc. This company is in the data sciences field aiming to improve the healthcare delivery through data acquisition and analysis. RediMinds specialize in collecting and organizing all patient centric clinical modalities, problem-specific data integration, and feature engineering. Their models augment the physician’s ability to predict disease vectors and effectively administer treatment protocols. We hear about what data science is and how it can be used in the healthcare space, the issue of explainability when it comes to AI, and the hinderances to interoperability in the current system. Listen to the podcast to learn about: • What data science is • The scope of the applications of data science in healthcare • The process of ‘digitizing’ the patient journey and how it can create predictability models • What the current extent of data science utilization is in the healthcare system • Mechanisms of building predictability models • How RediMinds validates their AI models • The issue of Explainability • Lack of interoperability in the current healthcare system • Creating a better understanding of disease through data science • Fragmentation issues in the healthcare data space • How the fear of new technology and liability hinders adoption rates • The potential role of data science in healthcare over the next decade • The future of RediMinds