東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Health information processing = eval...

CHIP (Conference) (2024 :)

Linked to FindBook

Google Book

Amazon

博客來

Health information processing = evaluation 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 processing/ edited 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:	CHIP (Conference)
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xvii, 228 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Medical informatics - Congresses. -
Online resource:	https://doi.org/10.1007/978-981-96-4298-4
ISBN:	9789819642984

Health information processing = evaluation 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 ;2458..

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

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

590642
Medical informatics
--Congresses.

LC Class. No.: R858.A2

Dewey Class. No.: 610.285

Health information processing = evaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings /
LDR:03717nmm a2200361 a 4500 001 2409674
003 DE-He213
005 20250413135151.0
006 m d
007 cr nn 008maaau
008 260204s2025 si s 0 eng d
020 $a 9789819642984 $q (electronic bk.)
020 $a 9789819642977 $q (paper)
024 7 $a 10.1007/978-981-96-4298-4 $2 doi
035 $a 978-981-96-4298-4
040 $a GP $c GP
041 0 $a eng
050 4 $a R858.A2
072 7 $a MBG $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a MED117000 $2 bisacsh
072 7 $a UXT $2 thema
082 0 4 $a 610.285 $2 23
090 $a R858.A2 $b C541 2024
111 2 $a CHIP (Conference) $n (10th : $d 2024 : $c Fuzhou, China) $3 3782979
245 1 0 $a Health information processing $h [electronic resource] : $b evaluation track papers : 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15-17, 2024 : proceedings / $c edited by Yanchun Zhang ... [et al.].
246 3 $a CHIP 2024
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a xvii, 228 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Communications in computer and information science, $x 1865-0937 ; $v 2458
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.
650 0 $a Medical informatics $v Congresses. $3 590642
650 0 $a Information resources management $v Congresses. $3 738076
650 1 4 $a Health Informatics. $3 892928
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Information Storage and Retrieval. $3 761906
700 1 $a Zhang, Yanchun. $3 900530
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Communications in computer and information science ; $v 2458. $3 3782992
856 4 0 $u https://doi.org/10.1007/978-981-96-4298-4
950 $a Computer Science (SpringerNature-11645)