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Full-Text Articles in Medicine and Health Sciences
Evaluating The Efficacy Of Chatgpt In Navigating The Spanish Medical Residency Entrance Examination (Mir): Promising Horizons For Ai In Clinical Medicine., Francisco Guillen-Grima, Sara Guillen-Aguinaga, Laura Guillen-Aguinaga, Rosa Alas-Brun, Luc Onambele, Wilfrido Ortega, Rocio Montejo, Enrique Aguinaga-Ontoso, Paul Barach, Ines Aguinaga-Ontoso
Evaluating The Efficacy Of Chatgpt In Navigating The Spanish Medical Residency Entrance Examination (Mir): Promising Horizons For Ai In Clinical Medicine., Francisco Guillen-Grima, Sara Guillen-Aguinaga, Laura Guillen-Aguinaga, Rosa Alas-Brun, Luc Onambele, Wilfrido Ortega, Rocio Montejo, Enrique Aguinaga-Ontoso, Paul Barach, Ines Aguinaga-Ontoso
Department of Medicine Faculty Papers
UNLABELLED: The rapid progress in artificial intelligence, machine learning, and natural language processing has led to increasingly sophisticated large language models (LLMs) for use in healthcare. This study assesses the performance of two LLMs, the GPT-3.5 and GPT-4 models, in passing the MIR medical examination for access to medical specialist training in Spain. Our objectives included gauging the model's overall performance, analyzing discrepancies across different medical specialties, discerning between theoretical and practical questions, estimating error proportions, and assessing the hypothetical severity of errors committed by a physician.
MATERIAL AND METHODS: We studied the 2022 Spanish MIR examination results after excluding …
Differentials And Predictors Of Food Insecurity Among Federally Qualified Health Center Target Populations In Philadelphia: A Cross-Sectional Study, Galicano Kai Inguito, Brandon Joa, James Gardner, Eric N Fung, Laura Layer, Karen Fritz
Differentials And Predictors Of Food Insecurity Among Federally Qualified Health Center Target Populations In Philadelphia: A Cross-Sectional Study, Galicano Kai Inguito, Brandon Joa, James Gardner, Eric N Fung, Laura Layer, Karen Fritz
Department of Medicine Faculty Papers
BACKGROUND: Over the past decade, the prevalence of food insecurity declined in the United States but curiously climbed in Philadelphia, Pennsylvania, a sizable metropolitan area where many households experience food insecurity and are dependent on programs like SNAP. Therefore, we aimed to determine the burden of food insecurity among populations near Philadelphia Federally Qualified Health Center (FQHC) clinic sites.
METHODS: This cross-sectional study was conducted in North Philadelphia, a populous and impoverished section of Philadelphia with many zip codes reporting 30-45% or more of the population below the federal poverty line. Students and clinicians affiliated with a local FQHC conducted …