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Health information processingevaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Health information processingedited by Yanchun Zhang ... [et al.].
Reminder of title:	evaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /
remainder title:	CHIP 2024
other author:	Zhang, Yanchun.
corporate name:
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xvii, 228 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Medical informaticsCongresses.
Online resource:	https://doi.org/10.1007/978-981-96-4298-4
ISBN:	9789819642984$q(electronic bk.)

Health information processingevaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /
Health information processingevaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /[electronic resource] :CHIP 2024edited by Yanchun Zhang ... [et al.]. - Singapore :Springer Nature Singapore :2025. - xvii, 228 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,24581865-0937 ;. - Communications in computer and information science ;229..

Syndrome Differentiation Thought in Traditional Chinese Medicine. -- Overview of the evaluation task for syndrome differentiation thought in traditional Chinese medicine in CHIP2024. -- Traditional Chinese Medicine Case Analysis System for High-Level Semantic Abstraction: Optimized with Prompt and RAG. -- A TCM Syndrome Differentiation Thinking Method Based on Chain of Thought and Knowledge Retrieval Augmentation. -- Fine-Tuning Large Language Models for Syndrome Differentiation in Traditional Chinese Medicine. -- Iterative Retrieval Augmentation for Syndrome Differentiation via Large Language Models. -- Lymphoma Information Extraction and Automatic Coding. -- Benchmark for Lymphoma Information Extraction and Automated Coding. -- Overview of the Lymphoma Information Extraction and Automatic Coding Evaluation Task in CHIP 2024. -- Automatic ICD Code Generation for Lymphoma Using Large Language Models. -- Lymphoma Tumor Coding and Information Extraction: A Comparative Analysis of Large Language Model-based Methods. -- Leveraging Chain of Thought for Automated Medical Coding of Lymphoma Cases. -- Harnessing Retrieval-Augmented LLMs for Training-Free Tumor Coding Classification. -- Hierarchical Information Extraction and Classification of Lymphoma Tumor Codes Based On LLM. -- Typical Case Diagnosis Consistenc. -- Benchmark of the Typical Case Diagnosis Consistency Evaluation Task in CHIP2024. -- Overview of the Typical Case Diagnosis Consistency Evaluation Task in CHIP2024. -- The Diagnosis of Typical Medical Cases through Optimized Fine-Tuning of Large Language Models. -- Utilizing Large Language Models Enhanced by Chain-of-Thought for the Diagnosis of Typical Medical Cases. -- Assessing Diagnostic Consistency in Clinical Cases: A Fine-Tuned LLM Voting and GPT Error Correction Framework. -- Typical Medical Case Diagnosis with Voting and Answer Discrimination using Fine-tuned LLM. -- Reliable Typical Case Diagnosis via Optimized Retrieval-Augmented Generation Techniques.

This book constitutes the refereed proceedings of the 10th China Health Information Processing Conference, CHIP 2024, held in Fuzhou, China, November 15-17, 2024. The CHIP 2024 Evaluation Track proceedings include 19 full papers which were carefully reviewed and grouped into these topical sections: syndrome differentiation thought in Traditional Chinese Medicine; lymphoma information extraction and automatic coding; and typical case diagnosis consistency.

ISBN: 9789819642984$q(electronic bk.)

Standard No.: 10.1007/978-981-96-4298-4doiSubjects--Topical Terms:

384533
Medical informatics
--Congresses.

LC Class. No.: R858.A2

Dewey Class. No.: 610.285

Health information processingevaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /
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505 0 $a Syndrome Differentiation Thought in Traditional Chinese Medicine. -- Overview of the evaluation task for syndrome differentiation thought in traditional Chinese medicine in CHIP2024. -- Traditional Chinese Medicine Case Analysis System for High-Level Semantic Abstraction: Optimized with Prompt and RAG. -- A TCM Syndrome Differentiation Thinking Method Based on Chain of Thought and Knowledge Retrieval Augmentation. -- Fine-Tuning Large Language Models for Syndrome Differentiation in Traditional Chinese Medicine. -- Iterative Retrieval Augmentation for Syndrome Differentiation via Large Language Models. -- Lymphoma Information Extraction and Automatic Coding. -- Benchmark for Lymphoma Information Extraction and Automated Coding. -- Overview of the Lymphoma Information Extraction and Automatic Coding Evaluation Task in CHIP 2024. -- Automatic ICD Code Generation for Lymphoma Using Large Language Models. -- Lymphoma Tumor Coding and Information Extraction: A Comparative Analysis of Large Language Model-based Methods. -- Leveraging Chain of Thought for Automated Medical Coding of Lymphoma Cases. -- Harnessing Retrieval-Augmented LLMs for Training-Free Tumor Coding Classification. -- Hierarchical Information Extraction and Classification of Lymphoma Tumor Codes Based On LLM. -- Typical Case Diagnosis Consistenc. -- Benchmark of the Typical Case Diagnosis Consistency Evaluation Task in CHIP2024. -- Overview of the Typical Case Diagnosis Consistency Evaluation Task in CHIP2024. -- The Diagnosis of Typical Medical Cases through Optimized Fine-Tuning of Large Language Models. -- Utilizing Large Language Models Enhanced by Chain-of-Thought for the Diagnosis of Typical Medical Cases. -- Assessing Diagnostic Consistency in Clinical Cases: A Fine-Tuned LLM Voting and GPT Error Correction Framework. -- Typical Medical Case Diagnosis with Voting and Answer Discrimination using Fine-tuned LLM. -- Reliable Typical Case Diagnosis via Optimized Retrieval-Augmented Generation Techniques.
520 $a This book constitutes the refereed proceedings of the 10th China Health Information Processing Conference, CHIP 2024, held in Fuzhou, China, November 15-17, 2024. The CHIP 2024 Evaluation Track proceedings include 19 full papers which were carefully reviewed and grouped into these topical sections: syndrome differentiation thought in Traditional Chinese Medicine; lymphoma information extraction and automatic coding; and typical case diagnosis consistency.
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