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Enhancing Precision in Detecting Severe Immune-Related Adverse Events: Comparative Analysis of Large Language Models and International Classification of Disease Codes in Patient Records.

Virginia H SunJulius C HeemelaarIbrahim HadzicVineet K RaghuChia-Yun WuLeyre ZubiriAzin GhamariNicole R LeBoeufOsama Abu-ShawerKenneth L KehlShilpa GroverPrabhsimranjot SinghGiselle Alexandra Suero-AbreuJessica WuAyo S FaladeKelley GrealishMolly F ThomasNora HathawayBenjamin D MedoffHannah K GilmanAlexandra-Chloé VillaniJor Sam HoMeghan J MooradianMeghan E SiseDaniel A ZlotoffSteven M BlumMichael L DouganRyan J SullivanTomas G NeilanKerry Lynn Reynolds
Published in: Journal of clinical oncology : official journal of the American Society of Clinical Oncology (2024)
LLMs are a useful tool for the detection of irAEs, outperforming ICD codes in sensitivity and adjudication in efficiency.
Keyphrases
  • machine learning
  • deep learning
  • case report
  • autism spectrum disorder
  • loop mediated isothermal amplification
  • early onset
  • real time pcr
  • label free
  • drug induced