Public articles linked to the same research event.
Studies in health technology and informatics This technical case report develops and evaluates a system that combines local large language models with rule-based validation against HUGO Gene Nomenclature to extract and structure mutational eligibility criteria from clinical trial records (identifying mutated genes, distinguishing inclusion from exclusion criteria, and assigning them to individual study arms); applied to 4,918 clinical trials it produced structured representations for 1,010 studies, and expert review of 42 trials showed 88.1% of studies correctly annotated with 80% precision at the level of individual eligibility criteria, with failures mainly due to hallucinated genes and misinterpreted abbreviations.
This technical case report develops and evaluates a system that combines local large language models with rule-based validation against HUGO Gene Nomenclature to extract and structure mutational eligibility criteria from clinical trial records (identifying mutated genes, distinguishing inclusion from exclusion criteria, and assigning them to individual study arms); applied to 4,918 clinical trials it produced structured representations for 1,010 studies, and expert review of 42 trials showed 88.1% of studies correctly annotated with 80% precision at the level of individual eligibility criteria, with failures mainly due to hallucinated genes and misinterpreted abbreviations.
This technical case report develops and evaluates a system that combines local large language models with rule-based validation against HUGO Gene Nomenclature to extract and structure mutational eligibility criteria from clinical trial records (identifying mutated genes, distinguishing inclusion from exclusion criteria, and assigning them to individual study arms); applied to 4,918 clinical trials it produced structured representations for 1,010 studies, and expert review of 42 trials showed 88.1% of studies correctly annotated with 80% precision at the level of individual eligibility criteria, with failures mainly due to hallucinated genes and misinterpreted abbreviations.
This technical case report develops and evaluates a system that combines local large language models with rule-based validation against HUGO Gene Nomenclature to extract and structure mutational eligibility criteria from clinical trial records (identifying mutated genes, distinguishing inclusion from exclusion criteria, and assigning them to individual study arms); applied to 4,918 clinical trials it produced structured representations for 1,010 studies, and expert review of 42 trials showed 88.1% of studies correctly annotated with 80% precision at the level of individual eligibility criteria, with failures mainly due to hallucinated genes and misinterpreted abbreviations.