Cédric Bousquet, Corneliu Henegar, Agnès Lillo-Le Louët, Patrice Degoulet, Marie-Christine Jaulent
Implementation of automated signal generation in pharmacovigilance using a knowledge-based approach
International journal of medical informatics
large language models llms chatgpt potential applications healthcare including dentistry priming practice providing llms initial relevant information approach improve output quality study aimed evaluate performance chatgpt 3 chatgpt 4 selfassessment questions dentistry swiss federal licensing examination dental medicine sfledm allergy clinical immunology european examination allergy clinical immunology eeaaci second objective assess impact priming chatgpts performance sfledm eeaaci multiplechoice questions university berns institute medical education platform administered chatgpt versions without priming performance analyzed based correct responses statistical analysis included wilcoxon rank sum tests alpha005 average accuracy rates sfledm eeaaci assessments 633 793 respectively chatgpt versions performed better eeaaci sfledm chatgpt 4 outperforming chatgpt 3 across tests chatgpt 3s performance exhibited significant improvement priming eeaaci p0017 sfledm p0024 assessments chatgpt 4 priming effect significant sfledm assessment p0038 performance disparity sfledm eeaaci assessments underscores chatgpts varying proficiency across different medical domains likely tied nature amount training data available field priming tool enhancing output especially earlier llms advancements chatgpt 3 4 highlight rapid developments llm technology yet use critical fields healthcare must remain cautious owing llms inherent limitations risks