Traditionally, precision medicine involves classifying patients to identify subpopulations that
respond favorably to specific therapeutics. We pose precision medicine as a dynamic …

Sepsis is a life-threatening condition affecting one million people per year in the US in which
dysregulation of the body's own immune system causes damage to its tissues, resulting in a …

Sepsis is a potentially life-threatening inflammatory response to infection or severe tissue
damage. It has a highly variable clinical course, requiring constant monitoring of the patient's …

Introduction In recent years, reinforcement learning (RL) has gained traction in the
healthcare domain. In particular, RL methods have been explored for haemodynamic …

Sepsis is a dangerous condition that is a leading cause of patient mortality. Treating sepsis
is highly challenging, because individual patients respond very differently to medical …

Sepsis is a leading cause of mortality in intensive care units and costs hospitals billions
annually. Treating a septic patient is highly challenging, because individual patients …

Abstract The potential of Reinforcement Learning (RL) has been demonstrated through
successful applications to games such as Go and Atari. However, while it is straightforward …

Guideline-based treatment for sepsis and septic shock is difficult because sepsis is a
disparate range of life-threatening organ dysfunctions whose pathophysiology is not fully …

Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because
individual patients respond differently to treatment. Thus, tailoring treatment to the individual …

Our aim is to establish a framework where reinforcement learning (RL) of optimizing
interventions retrospectively allows us a regulatory compliant pathway to prospective clinical …