Introducing L2M3, A Multilingual Medical Large Language Model to Advance Health Equity in Low-Resource Regions

arXiv:2404.08705v1 Announce Type: cross
Abstract: Addressing the imminent shortfall of 10 million health workers by 2030, predominantly in Low- and Middle-Income Countries (LMICs), this paper introduces an innovative approach that harnesses the power of Large Language Models (LLMs) integrated with machine translation models. This solution is engineered to meet the unique needs of Community Health Workers (CHWs), overcoming language barriers, cultural sensitivities, and the limited availability of medical dialog datasets. I have crafted a model that not only boasts superior …

abstract advance arxiv cs.ai cs.cl cs.lg equity health health equity income language language model language models large language large language model large language models llms low machine machine translation medical multilingual paper power solution translation type workers