Health Information Processing 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15–17, 2024, Proceedings, Part II /
This two-volume set CCIS 2432-2433 constitutes the refereed proceedings of the 10th China Health Information Processing Conference, CHIP 2024, held in Fuzhou, China, during November 15–17, 2024. The 32 full papers included in this set were carefully reviewed and selected from 65 submissions. They ar...
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| Altri autori: | , , , , , , , |
| Natura: | Elettronico eBook |
| Lingua: | inglese |
| Pubblicazione: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2025.
|
| Edizione: | 1st ed. 2025. |
| Serie: | Communications in Computer and Information Science,
2433 |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-981-96-3752-2 |
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| 245 | 1 | 0 | |a Health Information Processing |h [electronic resource] : |b 10th China Health Information Processing Conference, CHIP 2024, Fuzhou, China, November 15–17, 2024, Proceedings, Part II / |c edited by Yanchun Zhang, Qingcai Chen, Hongfei Lin, Lei Liu, Xiangwen Liao, Buzhou Tang, Tianyong Hao, Zhengxing Huang. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Singapore : |b Springer Nature Singapore : |b Imprint: Springer, |c 2025. | |
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| 490 | 1 | |a Communications in Computer and Information Science, |x 1865-0937 ; |v 2433 | |
| 505 | 0 | |a -- Mental health and disease prediction. -- Data Augmentation and Instruction Fine-Tuning for ADR Detection. -- Deep Fusion Network with Feature Engineering for Discharge Risk Assessment. -- Analysis of Risk Factors for Hemorrhagic Complications in Pediatric Acute Liver Failure. -- PMFNet: Pseudo-modal fusion network for obstructive sleep apnea detection using single-lead ECG signals. -- VisionLLM-based Multimodal Fusion Network for Glottic Carcinoma Early Detection. -- RAG Combined with Instruction Tuning for Traditional Chinese Medicine Syndrome Differentiation Thinking. -- Drug prediction and Knowledge map. -- MBF-DTI: A fused multi-dimensional biochemical feature-based drug target prediction method based on heterogeneous graph attention networks. -- Structure and pseudo-ligand based drug discovery for disease targets. -- Multi-channel hypergraph convolutional network predicts circRNA-drug sensitivity associations. -- Knowledge Infusion Framework with LLMs for Few-Shot Biomedical Relation Extraction. -- A review of drug-target interaction prediction methods. -- The Joint Entity-Relation Extraction Model Based on Span and Interactive Fusion Representation for Chinese Medical Texts with Complex Semantics. -- Multi-task learning-based knowledge graph question answering for pediatric epilepsy. -- Hypertension Medication Recommendation Based on Synergy and Selectivity of Heterogeneous Medical Entities. -- Integrating TCM's "One Root of Medicine and Food" Principle into Dietary Recommendations with Retrieval-Augmented LLMs. -- OAGLLM: A Retrieval-Augmented Large Language Model for Medication Instructions. | |
| 520 | |a This two-volume set CCIS 2432-2433 constitutes the refereed proceedings of the 10th China Health Information Processing Conference, CHIP 2024, held in Fuzhou, China, during November 15–17, 2024. The 32 full papers included in this set were carefully reviewed and selected from 65 submissions. They are organized in topical sections as follows: biomedical data processing and model application; mental health and disease prediction; and drug prediction and knowledge map. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 650 | 0 | |a Medical informatics. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Image processing |x Digital techniques. | |
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Application software. | |
| 650 | 0 | |a Information storage and retrieval systems. | |
| 650 | 1 | 4 | |a Health Informatics. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 650 | 2 | 4 | |a Computer and Information Systems Applications. |
| 650 | 2 | 4 | |a Information Storage and Retrieval. |
| 700 | 1 | |a Zhang, Yanchun. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Chen, Qingcai. |e editor. |0 (orcid)0000-0001-8473-7293 |1 https://orcid.org/0000-0001-8473-7293 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Lin, Hongfei. |e editor. |0 (orcid)0000-0003-0872-7688 |1 https://orcid.org/0000-0003-0872-7688 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Liu, Lei. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Liao, Xiangwen. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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