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| Link zu diesem Datensatz | https://d-nb.info/1354414853 |
| Titel | Large Language Models for Automatic Deidentification of Electronic Health Record Notes : International Workshop, IW-DMRN 2024, Kaohsiung, Taiwan, January 15, 2024, Revised Selected Papers / edited by Jitendra Jonnagaddala, Hong-Jie Dai, Ching-Tai Chen |
| Person(en) |
Jonnagaddala, Jitendra (Herausgeber) Dai, Hong-Jie (Herausgeber) Chen, Ching-Tai (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2025 |
| Verlag | Singapore : Springer Nature Singapore, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2025 |
| Umfang/Format | Online-Ressource, XII, 214 p. 93 illus., 61 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-981-9779-65-9 Printed edition:: ISBN: 978-981-9779-67-3 |
| Inhalt | -- Deidentification And Temporal Normalization of The Electronic Health Record Notes Using Large Language Models: The 2023 SREDH/AI-Cup Competition for Deidentification of Sensitive Health Information. -- Enhancing Automated De-identification of PathologyText Notes Using Pre-Trained Language Models. -- A Comparative Study of GPT3.5 Fine Tuning and Rule-Based Approaches for De-identification and Normalization of Sensitive Health Information in Electronic Medical Record Notes. -- Advancing Sensitive Health Data Recognition and Normalization through Large Language Model Driven Data Augmentation. -- Privacy Protection and Standardization of Electronic Medical Records Using Large Language Model. -- Applying Language Models for Recognizing and Normalizing Sensitive Information from Electronic Health Records Text Notes. -- Enhancing SHI Extraction and Time Normalization in Healthcare Records Using LLMs and Dual- Model Voting. -- Evaluation of OpenDeID Pipeline in the 2023 SREDH/AI-Cup Competition for Deidentification of Sensitive Health Information. -- Sensitive Health Information Extraction from EMR Text Notes: A Rule-Based NER Approach Using Linguistic Contextual Analysis. -- A Hybrid Approach to the Recognition of Sensitive Health Information: LLM and Regular Expressions. -- Patient Privacy Information Retrieval with Longformer and CRF, Followed by Rule-Based Time Information Normalization: A Dual-Approach Study. -- A Deep Dive into the Application of Pythia for Enhancing Medical Information De-identification in the AI CUP 2023. -- Utilizing Large Language Models for Privacy Protection and Advancing Medical Digitization. -- Comprehensive Evaluation of Pythia Model Efficiency in De-identification and Normalization for Enhanced Medical Data Management. -- A Two-stage Fine-tuning Procedure to Improve the Performance of Language Models in Sensitive Health Information Recognition and Normalization Tasks |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2501260305444.172331840868 DOI: 10.1007/978-981-97-7966-6 |
| URL | https://doi.org/10.1007/978-981-97-7966-6 |
| ISBN/Einband/Preis | 978-981-97-7966-6 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Communications in Computer and Information Science ; 2148 |
| DDC-Notation | 610.28 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 610 Medizin, Gesundheit |
| Online-Zugriff | Archivobjekt öffnen |
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