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Health Information Processing. Evaluation Track Papers: 8th China Conference, CHIP 2022, Hangzhou, China, October 2123, 2022, Revised Selected Papers 1st ed. 2023 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 230 pages, height x width: 235x155 mm, weight: 385 g, 50 Illustrations, color; 8 Illustrations, black and white; XV, 230 p. 58 illus., 50 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1773
  • Izdošanas datums: 22-Jul-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819948258
  • ISBN-13: 9789819948253
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Health Information Processing. Evaluation Track Papers: 8th China Conference, CHIP 2022, Hangzhou, China, October 2123, 2022, Revised Selected Papers 1st ed. 2023Palielināt
  • Formāts: Paperback / softback, 230 pages, height x width: 235x155 mm, weight: 385 g, 50 Illustrations, color; 8 Illustrations, black and white; XV, 230 p. 58 illus., 50 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1773
  • Izdošanas datums: 22-Jul-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819948258
  • ISBN-13: 9789819948253
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819948253.html
Keywords:
This book constitutes the papers presented at the Evaluation Track of the 8th China Conference on Health Information Processing, CHIP 2022, held in Hangzhou, China during  October 21–23, 2022.

The 20 full papers included in this book were carefully reviewed and selected from 20 submissions. They were organized in topical sections as follows: text mining for gene-disease association semantic; medical causal entity and relation extraction; medical decision tree extraction from unstructured text; OCR of electronic medical document; clinical diagnostic coding.
Text Mining for Gene-Disease Association Semantic.- Text Mining Task for
Gene-Disease Association Semantics in CHIP 2022.- Hierarchical Global
Pointer Network: An Implicit Relation Inference Method for
Gene-Disease Knowledge Discovery.- A Knowledge-based Data Augmentation
Framework for Few-Shot Biomedical Information Extraction.- Biomedical Named
Entity Recognition Under Low-Resource Situation.- Medical Causal Entity and
Relation Extraction.- CHIP2022 Shared Task Overview: Medical Causal Entity
Relationship Extraction.- Domain Robust Pipeline for Medical Causal Entity
and Relation Extraction Task.- A Multi-span-based Conditional Information
Extraction Model.- Medical Causality Extraction: A Two-Stage Based Nested
Relation Extraction Model.- Medical Decision Tree Extraction from
Unstructured Text.- Extracting Decision Trees from Medical Texts: an Overview
of the Text2DT Track in CHIP2022.- Medical Decision Tree Extraction: A Prompt
Based Dual Contrastive Learning Method.- An automatic construction method of
diagnosis and treatment decision tree based on UIE and
logical rules.- Research on Decision Tree Method of Medical Text Based on
Information Extraction.- OCR of Electronic Medical Document.- Information
extraction of Medical Materials: an Overview of the track of Medical
Material MedOCR.- TripleMIE: Multi-Modal and Multi architecture Information
Extraction.- Multimodal end-to-end visual document parsing.- Improving
Medical OCR Information Extraction with Integrated Bert and LayoutXLM
Models.- Clinical Diagnostic Coding.- Overview of CHIP 2022 Shared Task 5:
Clinical Diagnostic Coding.- Clinical Coding Based on Knowledge Enhanced
Language Model and Attention Pooling.- Rule-enhanced Disease Coding Method
based on Roberta.- Diagnosis Coding Rule-Matching Based on Characteristic
Words and Dictionaries.