Developing a Large Language Model (LLM) for Interaction with Community Health Workers (CHWs) in the Prevention of Non-Communicable Diseases (NCDs) in the First 1000 Days of Life in the Brazilian Unified Health System (SUS)

Cecília Claudia Costa Ribeiro of Universidade Federal do Maranhão in Brazil will develop an LLM to help frontline healthcare workers identify risks and take action to prevent NCDs in the first 1000 days of life. There are connections between NCDs in early childhood that are affected by social inequities as well as pregnancy-associated factors. They will apply machine learning algorithms to data for women during and shortly after pregnancy to build risk prediction models of NCDs for children in the BRISA Cohort of São Luís, with predictor variables encompassing socioeconomic, behavioral, and biological stressors. The estimated risks will be input to an LLM that incorporates the best available scientific evidence on each NCD. This LLM, when given data from women patients, can then determine the risk of NCDs for the patient’s children, along with an explanation to help CHWs effectively communicate these risks and make evidence-based recommendations in real-time for prevention of NCDs.