MedMobile: A mobile-sized language model with expert-level clinical capabilities
Language models (LMs) have demonstrated expert-level reasoning and recall abilities in medicine. However, computational costs and privacy concerns are mounting barriers to wide-scale implementation. We introduce a parsimonious adaptation of phi-3-mini, MedMobile, a 3.8 billion parameter LM capable o...
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Zusammenfassung: | Language models (LMs) have demonstrated expert-level reasoning and recall
abilities in medicine. However, computational costs and privacy concerns are
mounting barriers to wide-scale implementation. We introduce a parsimonious
adaptation of phi-3-mini, MedMobile, a 3.8 billion parameter LM capable of
running on a mobile device, for medical applications. We demonstrate that
MedMobile scores 75.7% on the MedQA (USMLE), surpassing the passing mark for
physicians (~60%), and approaching the scores of models 100 times its size. We
subsequently perform a careful set of ablations, and demonstrate that chain of
thought, ensembling, and fine-tuning lead to the greatest performance gains,
while unexpectedly retrieval augmented generation fails to demonstrate
significant improvements |
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DOI: | 10.48550/arxiv.2410.09019 |