HOW CAN HEALTH STARTUPS ACCESS MORE DATA TO SCALE?

The discussion highlights the importance of accurate and diverse data in transforming healthcare, emphasizing that no valuable business has yet been built on Apple Health due to non-continuous and sometimes inaccurate data. It stresses the need for unique data sets to maintain a competitive advantage in AI healthcare companies, as large language models become commoditized. The role of AI in assessing and processing health data is crucial, with collaboration across the industry being key. The discussion also points out the staggering statistic that 97% of medical research has been done on men, prompting a pledge for equal research allocation between genders. The integration of AI into healthcare startups' operations is discussed, with a focus on data quality and leveraging AI in workflows. Governance of AI models and data protection is emphasized to prevent information leaks and ensure quality outputs. The importance of personalized data for personalized medicine is highlighted, with a call for more diverse research and data sample sets. The discussion also touches on the rapid advancement in the field and the need for accessible tools for researchers. Lastly, the potential of sports as public health vehicles and the application of data in novel ways for well-being are mentioned.