The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care

The authors of this journal article state that sepsis is the third leading cause of death worldwide and the main cause of mortality in hospitals, but the best treatment strategy remains uncertain. In particular, evidence suggests that current practices in the administration of intravenous fluids and vasopressors are suboptimal and likely induce harm in a proportion of patients. To tackle this sequential decision-making problem, the authors developed a reinforcement learning agent, the Artificial Intelligence (AI) Clinician, which extracted implicit knowledge from an amount of patient data that exceeds by many-fold the life-time experience of human clinicians and learned optimal treatment by analyzing a myriad of (mostly suboptimal) treatment decisions. They demonstrate that the value of the AI Clinician ' s selected treatment is on average reliably higher than human clinicians. In a large validation cohort independent of the training data, mortality was lowest in patients for whom clinicians ' actual doses matched the AI decisions. The model provides individualized and clinically interpretable treatment decisions for sepsis that could improve patient outcomes.
Source: Current Awareness Service for Health (CASH) - Category: Consumer Health News Source Type: news