Towards Fair and Efficient De-identification: Quantifying the Efficiency and Generalizability of De-identification Approaches

Documenti analoghi

• Not What the Doctor Ordered: Surveying LLM-based De-identification and Quantifying Clinical Information Loss
  di: Aghakasiri, Kiana, et al.
  Pubblicazione: (2025)
• AIOptimizer - Software performance optimisation prototype for cost minimisation
  di: Zambare, Noopur
  Pubblicazione: (2023)
• In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
  di: Xiao, Yuxin, et al.
  Pubblicazione: (2023)
• Thunder-DeID: Accurate and Efficient De-identification Framework for Korean Court Judgments
  di: Hahm, Sungeun, et al.
  Pubblicazione: (2025)
• Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs
  di: Tavakoli, Mohammad, et al.
  Pubblicazione: (2025)