CNA: An AI-Oriented Comprehensive Normalized Assessment for Healthy Status and Application to Optimize RRT Strategies by Reinforcement Learning
Read the original on arXiv Machine Learning →The paper introduces CNA, an AI‑oriented comprehensive normalized assessment that transforms vital‑sign distributions into a standard normal space to produce a unified health‑status score. This score serves as a criterion for evaluating and terminating reinforcement learning policies in Renal Replacement Therapy (RRT). Using a 23‑dimensional state representation and matrix decomposition to handle missing data, the authors apply offline RL algorithms and show that the learned strategy reduces mortality from 13.2% to 5.0% and shortens hospital stays by nearly 59 hours compared to physician‑observed treatments.
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