DBTB INT Eric Williams r
summary
Claims that the same analytics, machine learning and experimentation stack used to optimize clicks can be repurposed to optimize health outcomes, replacing ad metrics with treatment success and cost savings. Describes a Netflix‑style self‑learning system that ties biology, genomics and cancer histologies plus activity and social data to outcomes, enabling personalization as more patients are treated. Argues for outcomes‑based pricing and better interoperability, and stresses training on diverse datasets so statistical intuition—not hype—guides decisions.
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