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Large Language Models for Automatic Deidentification of Sensitive Health Information in Clinical Speech : 2025 International Workshop on Deidentification of Electronic Medical Record Notes (2025 IW-DMRN), Taipei, Taiwan, August 10, 2025, Revised Selected Papers.
Springer Nature - Springer Computer Science eBooks 2026 English International Available online
View online- Format:
- Book
- Author/Creator:
- Jonnagaddala, Jitendra.
- Series:
- Communications in Computer and Information Science Series
- Communications in Computer and Information Science Series ; v.2908
- Language:
- English
- Physical Description:
- 1 online resource (202 pages)
- Edition:
- 1st ed.
- Place of Publication:
- Singapore : Springer, 2026.
- Summary:
- This volume constitutes the refereed proceedings of the 2025 International Workshop on Deidentification of Electronic Health Record Notes, IW-DMRN 2025, held in Taipei, Taiwan, during August 10, 2025.The 9 full papers were included in this were carefully reviewed and selected from 25 submissions.
- Contents:
- Communications in Computer and Information Science
- Large Language Models for Automatic Deidentification of Sensitive Health Information in Clinical Speech
- Preface
- Organization
- Contents
- Instruction-Tuned LLMs for Multilingual Medical ASR and Privacy Entity Extraction
- Temporal Subword De-Identification of Medical Speech for Privacy Protection Leveraging ASR and LLMs
- Prompt Engineering and Post-Processing for Sensitive Health Information Recognition
- Named Entity Recognition in Chinese-English Speech Using Automatic Speech Recognition and Large Language Models
- A Two-Stage Generative Framework for Sensitive Health Information Extraction and Temporal Normalization in Medical Records
- Recognition of Sensitive Personal Data in Doctor-Patient Speech
- Multistage Automatic Speech Recognition- Named Entity Recognition Framework for Privacy Sensitive Information Recognition in Medical Speech Data
- Speech De-identification of Chinese, English and Minnan: Effectiveness of Chinese-based LLM Model and ASR
- A Generative Large Language Model-based Approach for Sensitive Data Identification in Medical Speech
- Author Index.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 9789819222827
- OCLC:
- 1603127894
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