@ShahidNShah
At-home rehabilitation for post-stroke patients presents significant challenges, as continuous, personalized care is often limited outside clinical settings. Moreover, the lack of integrated solutions capable of simultaneously monitoring motor recovery and providing intelligent assistance in home environments hampers rehabilitation outcomes.
Specialized “medical” versions of large language models do not consistently outperform their general-purpose counterparts on many clinical question-answering tasks, challenging the assumption that domain-specific pretraining automatically leads to better healthcare AI. The findings indicate that leading general AI models may already possess substantial medical reasoning capabilities.
Continue reading at arxiv.org
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