AI Assisted Triage for Clinical Decision Making in Hematology Oncology
Jul 1, 2025·
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1 min read
Naif A. Ganadily
Abstract
Orchestrating an end-to-end Generative AI and Rule Based system pipeline to replicate the full triage system of Classical Hematology Oncology. This work combines the reasoning capabilities of Large Language Models with established clinical protocols to assist healthcare professionals in making faster, more accurate clinical decisions.
Type
Status: Pending Publication
This research develops a hybrid AI system that combines Generative AI with rule-based approaches to automate and enhance the triage process in hematology oncology. The system aims to maintain the rigor and safety standards of traditional medical protocols while providing faster decision support to clinicians.
Key Contributions:
- End-to-end automated triage pipeline for hematology oncology
- Integration of LLM reasoning with established clinical rules
- Designed to assist rather than replace clinical expertise
Affiliation: Mayo Clinic, Scottsdale Campus & Arizona State University
