Please wait a minute...
Data Analysis and Knowledge Discovery
Current Issue | Archive | Adv Search |
Knowledge Discovery of Diseases Based on SPO Predications
Cai Miaozhi,Li Xiaoying,Zhao Jiawei,Feng Fengxiang,Ren Huiling
(Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100020, China)
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Object] This study tries to discover knowledge from the high-level evidence-based diseases literature collected by PubMed, aiming to provide reference for clinical diagnosis and treatment and daily prevention and control of diseases. [Methods] We proposed a diseases knowledge discovery model based on SPO predications with the semantic extraction tool SemRep. Then we selected the diabetes-related literature to verify the model, and discovered knowledge based on SPO visualization and clinical knowledge. [Results] 1,258 SPO predications and 16 semantic relationships were obtained, and diabetes-related genes, common complications, detection and treatment methods were revealed. [Limitations] The data source of this study is limited, ignoring the real-world data such as knowledge bases and electronic medical records. [Conclusion] It verified the feasibility of the diseases knowledge model based on SPO predication to discover the biomedical knowledge in literature, which is helpful to provide potential research hypotheses and ideas for biomedical researchers.

Key words SPO      diabetes mellitus      knowledge discovery      knowledge organization      
Published: 12 October 2021
ZTFLH:   
  font-family:"  
  G250
" target="_blank">"> G250
 

Cite this article:

Cai Miaozhi, Li Xiaoying, Zhao Jiawei, Feng Fengxiang, Ren Huiling. Knowledge Discovery of Diseases Based on SPO Predications . Data Analysis and Knowledge Discovery, 0, (): 1-.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467. 2021.0612     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y0/V/I/1

[1] Dai Bing,Hu Zhengyin. Review of Studies on Literature-Based Discovery[J]. 数据分析与知识发现, 2021, 5(4): 1-12.
[2] Shen Wang, Li Shiyu, Liu Jiayu, Li He. Optimizing Quality Evaluation for Answers of Q&A Community[J]. 数据分析与知识发现, 2021, 5(2): 83-93.
[3] Zhao Ping,Sun Lianying,Tu Shuai,Bian Jianling,Wan Ying. Identifying Scenic Spot Entities Based on Improved Knowledge Transfer[J]. 数据分析与知识发现, 2020, 4(5): 118-126.
[4] Hu Zhengyin,Liu Leilei,Dai Bing,Qin Xiaochu. Discovering Subject Knowledge in Life and Medical Sciences with Knowledge Graph[J]. 数据分析与知识发现, 2020, 4(11): 1-14.
[5] Haixia Sun,Panpan Deng,Jiao Li,Liu Shen,Qing Qian. Automatic Concept Update Strategy Towards Heterogeneous Terminology Integration[J]. 数据分析与知识发现, 2020, 4(1): 121-130.
[6] Jiahui Hu,An Fang,Wanqing Zhao,Chenliu Yang,Huiling Ren. Annotating Chinese E-Medical Record for Knowledge Discovery[J]. 数据分析与知识发现, 2019, 3(7): 123-132.
[7] Juhua Wu,Yu Wang,Ming Li,Shaoyun Cai. Knowledge Discovery of Online Health Communities with Weighted Knowledge Network[J]. 数据分析与知识发现, 2019, 3(2): 108-117.
[8] Lei Yang,Zirun Wang,Guisheng Hou. Discovering Topics of Online Health Community with Q-LDA Model[J]. 数据分析与知识发现, 2019, 3(11): 52-59.
[9] Jiying Hu,Jing Xie,Li Qian,Changlei Fu. Constructing Big Data Platform for Sci-Tech Knowledge Discovery with Knowledge Graph[J]. 数据分析与知识发现, 2019, 3(1): 55-62.
[10] Wang Zhongyi,Zhang Heming,Huang Jing,Li Chunya. Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis[J]. 数据分析与知识发现, 2018, 2(11): 80-94.
[11] Wang Xin,Feng Wen’gang. Review of Techniques Detecting Online Extremism and Radicalization[J]. 数据分析与知识发现, 2018, 2(10): 2-8.
[12] Zhang Zhiqiang,Fan Shaoping,Chen Xiujuan. Biomedical Informatics Studies for Knowledge Discovery in Precision Medicine[J]. 数据分析与知识发现, 2018, 2(1): 1-8.
[13] Mu Dongmei,Wang Ping,Zhao Danning. Reducing Data Dimension of Electronic Medical Records: An Empirical Study[J]. 数据分析与知识发现, 2018, 2(1): 88-98.
[14] Yang Chaofan,Deng Zhonghua,Peng Xin,Liu Bin. Review of Information Retrieval Research: Case Study of Conference Papers[J]. 数据分析与知识发现, 2017, 1(7): 35-43.
[15] Xie Jing,Wang Jingdong,Wu Zhenxin,Zhang Zhixiong,Wang Ying,Ye Zhifei. Building Semantic Enrichment Framework for Scientific Literature Retrieval System[J]. 数据分析与知识发现, 2017, 1(4): 84-93.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn