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Health Information Processing. Evaluation Track Papers: 8th China Conference, CHIP 2022, Hangzhou, China, October 21–23, 2022, Revised Selected Papers de Buzhou Tang

Health Information Processing. Evaluation Track Papers: 8th China Conference, CHIP 2022, Hangzhou, China, October 21–23, 2022, Revised Selected Papers: Communications in Computer and Information Science, cartea 1773

Editat de Buzhou Tang, Qingcai Chen, Hongfei Lin, Fei Wu, Lei Liu, Tianyong Hao, Yanshan Wang, Haitian Wang, Jianbo Lei, Zuofeng Li, Hui Zong
en Limba Engleză Paperback – 22 iul 2023
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.
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Specificații

ISBN-13: 9789819948253
ISBN-10: 9819948258
Pagini: 230
Ilustrații: XV, 230 p. 58 illus., 50 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.35 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Singapore, Singapore

Cuprins

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.