Public articles linked to the same research event.
Journal of medical systems This report develops CLASS, a Python-based modular large language model pipeline that runs within a secure institutional environment and combines expert-curated concept lists, a task-specific prompt suite, and a schema-constrained output format to extract structured data from clinical notes, and evaluates it exploratorily on a single-center retrospective corpus of pediatric esophageal airway treatment surgery (EATS) operative notes: observed concordance with surgeon adjudication on the 20 longest notes (3,960 note-procedure pairs) was high (F1 0.9967), while CLASS proposed 28 candidate procedure variants or additions, 18 (64.
This report develops CLASS, a Python-based modular large language model pipeline that runs within a secure institutional environment and combines expert-curated concept lists, a task-specific prompt suite, and a schema-constrained output format to extract structured data from clinical notes, and evaluates it exploratorily on a single-center retrospective corpus of pediatric esophageal airway treatment surgery (EATS) operative notes: observed concordance with surgeon adjudication on the 20 longest notes (3,960 note-procedure pairs) was high (F1 0.9967), while CLASS proposed 28 candidate procedure variants or additions, 18 (64.
This report develops CLASS, a Python-based modular large language model pipeline that runs within a secure institutional environment and combines expert-curated concept lists, a task-specific prompt suite, and a schema-constrained output format to extract structured data from clinical notes, and evaluates it exploratorily on a single-center retrospective corpus of pediatric esophageal airway treatment surgery (EATS) operative notes: observed concordance with surgeon adjudication on the 20 longest notes (3,960 note-procedure pairs) was high (F1 0.9967), while CLASS proposed 28 candidate procedure variants or additions, 18 (64.
This report develops CLASS, a Python-based modular large language model pipeline that runs within a secure institutional environment and combines expert-curated concept lists, a task-specific prompt suite, and a schema-constrained output format to extract structured data from clinical notes, and evaluates it exploratorily on a single-center retrospective corpus of pediatric esophageal airway treatment surgery (EATS) operative notes: observed concordance with surgeon adjudication on the 20 longest notes (3,960 note-procedure pairs) was high (F1 0.9967), while CLASS proposed 28 candidate procedure variants or additions, 18 (64.