Bayesian Modeling and Causal Inference
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Abstract
Abstract
The objective of this paper is to understand what characteristics and features of clinical data influence physician's decision about ordering laboratory tests or prescribing medications the most. We conduct our analysis on data and decisions extracted from electronic health records of 4486 post-surgical cardiac patients. The summary statistics for 335 different lab order decisions and 407 medication decisions are reported. We show that in many cases, physician's lab-order and medication decisions are predicted well by simple patterns such as last value of a single test result, time since a certain lab test was ordered or time since certain procedure was executed.
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@article{Vako2026Feature,
title = {Feature importance analysis for patient management decisions},
author = {Michal Vaľko and Miloš Hauskrecht},
journal = {PubMed},
year = {2026},
doi = {10.48550/arxiv.2605.04666},
url = {https://pubmed.ncbi.nlm.nih.gov/20841808}
}FAQ
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