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Towards an Explainable Framework for Personalized Treatment Recommendations
0
Zitationen
3
Autoren
2025
Jahr
Abstract
Most Clinical Decision Support Systems (CDSS) focus on diagnosis, offering limited help with personalized treatment. Although large language models (LLMs) show promise in clinical reasoning, integrating Clinical Practice Guidelines (CPGs) with patient-specific Electronic Health Records (EHRs) remains a challenge. Many systems also lack transparency, limiting clinician trust. This work proposes a lightweight, modular CDSS that fuses insights from CPGs and EHRs to generate treatment recommendations tailored to individual patients, with a clear emphasis on explainability.
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