Health Information Processing. Evaluation Track Papers [electronic resource] : 8th China Conference, CHIP 2022, Hangzhou, China, October 21-23, 2022, Revised Selected Papers / edited by Buzhou Tang, Qingcai Chen, Hongfei Lin, Fei Wu, Lei Liu, Tianyong Hao, Yanshan Wang, Haitian Wang, Jianbo Lei, Zuofeng Li, Hui Zong.

Colaborador(es): Tang, Buzhou [editor.] | Chen, Qingcai [editor.] | Lin, Hongfei [editor.] | Wu, Fei [editor.] | Liu, Lei [editor.] | Hao, Tianyong [editor.] | Wang, Yanshan [editor.] | Wang, Haitian [editor.] | Lei, Jianbo [editor.] | Li, Zuofeng [editor.] | Zong, Hui [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Communications in Computer and Information Science ; 1773Editor: Singapore : Springer Nature Singapore : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: XV, 230 p. 58 illus., 50 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819948260Tema(s): Medical informatics | Artificial intelligence | Image processing -- Digital techniques | Computer vision | Application software | Information storage and retrieval systems | Health Informatics | Artificial Intelligence | Computer Imaging, Vision, Pattern Recognition and Graphics | Computer and Information Systems Applications | Information Storage and RetrievalFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 610.285 Clasificación LoC:R858-859.7Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer Nature eBookResumen: 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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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.

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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