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An Agentic OODA Framework for Transparent End to End Clinical Decision Support

2026-08-03

Abstract excerpt

<title>Abstract</title> <p>Artificial Intelligence (AI) agents are increasingly being explored for automation purposes in healthcare applications. However, their deployment raises concerns regarding the reliability, usability, and trustworthiness in clinical decision support. In particular, Large Language Model (LLM) based systems often exhibit variability between different runs on the same input, which makes the...

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Literature Corpus work
42d6d703-06c7-5562-a68d-f18821331ea5
DOI
10.21203/rs.3.rs-10426136/v1
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An Agentic OODA Framework for Transparent End to End Clinical Decision SupportDOI 10.21203/rs.3.rs-10426136/v1
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