Learning to Treat Sepsis with Multi-Output Gaussian Process Deep Recurrent Q-Networks

no code implementations • ICLR 2018 • Joseph Futoma, Anthony Lin, Mark Sendak, Armando Bedoya, Meredith Clement, Cara O'Brien, Katherine Heller

We evaluate our approach on a heterogeneous dataset of septic spanning 15 months from our university health system, and find that our learned policy could reduce patient mortality by as much as 8. 2\% from an overall baseline mortality rate of 13. 3\%.

Gaussian Processes reinforcement-learning +3