MIO: An ontology for annotating and integrating medical knowledge in myocardial infarction to enhance clinical decision making.

Journal: Computers in biology and medicine
PMID: 40174503

Abstract

As biotechnology and computer science continue to advance, there's a growing amount of biomedical data worldwide. However, standardizing and consolidating these data remains challenging, making analysis and comprehension more difficult. To enhance research on complex diseases like myocardial infarction (MI), an ontology is necessary to ensure consistent data labeling and knowledge representation. This will facilitate data management and the application of artificial intelligence techniques in this field, ultimately advancing precision medicine research for MI. This study introduced the MI Ontology (MIO), which was developed using Stanford's seven-step method and Protégé. MIO aims to support precision medicine research on MI by effectively modeling and representing MI-related concepts and relationships. The validation of the MIO model involved employing Ontology Web Language (OWL) reasoners and comparing it with other disease-specific ontologies. MIO is an ontology model comprising of 3090 classes, 14 object attributes, 3494 individuals, 9415 synonyms and 49263 axioms, which encompass knowledge related to MI such as anatomical entities, clinical findings, drugs, genes, influencing factors, pathogenesis, patients-related concepts, procedures, and disease types. Furthermore, MIO has passed logical consistency validation and exhibits a broader conceptual scope and deeper knowledge structure than other disease-specific ontologies. Additionally, clinical use scenarios for MIO were developed to help address specific clinical problems. This study constructed the first comprehensive disease-specific ontology in cardiovascular diseases, named MIO, to promote precision medicine research on MI. MIO integrates and standardizes medical data, addressing complexity and standardization challenges. This promotes the use of big data analysis, explainable AI, and deep phenotype research in precision medicine. Future efforts will focus on enhancing and expanding MIO's applicability and scalability for superior services in this field.

Authors

  • Chaoying Zhan
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
  • Shumin Ren
    Institutes for Systems Genetics, Frontiers Science Centre for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Yuxin Zhang
    State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology , Sichuan University , Chengdu 610041 , People's Republic of China.
  • Xiaojun Lv
    Department of Cardiology, West China Hospital, Sichuan University, Chengdu, 610212, Sichuan, China.
  • Yalan Chen
    Center for Systems Biology, Soochow University, Suzhou 215006, China.
  • Xin Zheng
    Department of Clinical Laboratory, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: dearjanna@126.com.
  • Rongrong Wu
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
  • Erman Wu
    Department of Urology and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610212, China.
  • Tong Tang
    Institutes for Systems Genetics, Frontiers Science Centre for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
  • Jiao Wang
    Key Lab of Cell Differentiation and Apoptosis of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Cheng Bi
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
  • Mengqiao He
    Department of Pharmacy and Institutes for Systems Genetics, West China Hospital, Sichuan University, Frontiers Science Center for Disease-Related Molecular Network, Xinchuan Road 2222, Chengdu 610041, China.
  • Xingyun Liu
    Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, Sichuan, China; Center for Systems Biology, Soochow University, Suzhou 215006, Jiangsu, China.
  • Ke Zhang
    Center for Radiation Oncology, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, Hangzhou 310001, China.
  • Yingbo Zhang
    Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, 610212, Sichuan, China; Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China.
  • Bairong Shen
    Institute of Systems Genetics, Department of Critical Care Medicine, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, China.

Keywords

External Resources

Popular Topics
Recent Journals