Smart Imitator: Learning from Imperfect Clinical Decisions.

ABSTRACT:

Objectives

This study introduces Smart Imitator (SI), a 2-phase reinforcement learning (RL) solution enhancing personalized treatment policies in healthcare, addressing challenges from imperfect clinician data and complex environments.

Materials and methods

Smart Imitator's first phase uses adversarial cooperative imitation learning with a novel sample selection schema to categorize clinician policies from optimal to nonoptimal. The second phase creates a parameterized reward function to guide the learning of superior treatment policies through RL. Smart Imitator's effectiveness was validated on 2 datasets: a sepsis dataset with 19 711 patient trajectories and a diabetes dataset with 7234 trajectories.

Results

Extensive quantitative and qualitative experiments showed

SUBMITTER: Perera D 

PROVIDER: S-EPMC12758472 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature