Towards an Explainable Framework for Personalized Treatment Recommendations
Labraoui, Mohamed Ouassim Benzadri, Zakaria
Labraoui, Mohamed Ouassim
Benzadri, Zakaria
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2026-01-05
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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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