3 papers
cs.IR2026
A Hybrid Retrieval and Reranking Framework for Evidence-Grounded Retrieval-Augmented Generation
Fariba Afrin Irany, Sampson Akwafuo
Retrieval-augmented generation (RAG) improves large language model reliability by grounding generated responses in external evidence. However, RAG performance depends on the releva…
cs.CL2026
Selective Fine-Tuning of GPT Architectures for Parameter-Efficient Clinical Text Classification
Fariba Afrin Irany, Sampson Akwafuo
The rapid expansion of electronic health record (EHR) systems has generated large volumes of unstructured clinical narratives that contain valuable information for disease identifi…
cs.CL2026
From Generative Modeling to Clinical Classification: A GPT-Based Architecture for EHR Notes
Fariba Afrin Irany, Sampson Akwafuo
The increasing availability of unstructured clinical narratives in electronic health records (EHRs) has created new opportunities for automated disease characterization, cohort ide…