SHIELD dataset and distilled DeBERTa v3 model achieve 0.88 micro precision and 0.86 recall on PHI de-identification while matching teacher performance on structured categories.
DeID - GPT : Zero -shot Medical Text De - Identification by GPT -4, December 2023
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LLaMA-XR fine-tunes LLaMA 3.1 with QLoRA on DenseNet-121 embeddings to generate radiology reports from chest X-rays, reporting ROUGE-L of 0.433 and METEOR of 0.336 on the IU X-ray benchmark.
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.
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SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification
SHIELD dataset and distilled DeBERTa v3 model achieve 0.88 micro precision and 0.86 recall on PHI de-identification while matching teacher performance on structured categories.
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LLaMA-XR: A Novel Framework for Radiology Report Generation using LLaMA and QLoRA Fine Tuning
LLaMA-XR fine-tunes LLaMA 3.1 with QLoRA on DenseNet-121 embeddings to generate radiology reports from chest X-rays, reporting ROUGE-L of 0.433 and METEOR of 0.336 on the IU X-ray benchmark.
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Data-Centric Foundation Models in Computational Healthcare: A Survey
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.