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Evolution of publicly available large language models for complex decision-making in breast cancer care.

Sebastian GriewingJohannes KnitzaJelena BoekhoffChristoph HillenFabian LechnerUwe WagnerMarkus WallwienerSebastian Kuhn
Published in: Archives of gynecology and obstetrics (2024)
This early feasibility study is the first to compare different LLM in breast cancer care with regard to changes in accuracy over time, i.e., with access to more data or through technological upgrades. Methodological advancement, i.e., the optimization of prompting techniques, and technological development, i.e., enabling data input control and secure data processing, are necessary in the preparation of large-scale and multicenter studies to provide evidence on their safe and reliable clinical application. At present, safe and evidenced use of LLM in clinical breast cancer care is not yet feasible.
Keyphrases
  • electronic health record
  • big data
  • autism spectrum disorder
  • machine learning
  • data analysis
  • high resolution
  • deep learning
  • case control
  • simultaneous determination