Articles producció científica> Enginyeria Informàtica i Matemàtiques

Multi-level medical knowledge formalization to support medical practice for chronic diseases

  • Identification data

    Identifier: imarina:5133239
  • Authors:

    Kamisalic, Aida
    Riano, David
    Kert, Suzana
    Welzer, Tatjana
    Zlatolas, Lili Nemec
  • Others:

    Author, as appears in the article.: Kamisalic, Aida; Riano, David; Kert, Suzana; Welzer, Tatjana; Zlatolas, Lili Nemec
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: RIAÑO RAMOS, DAVID
    Keywords: Medical procedural knowledge Knowledge representation Decision support systems Decision making
    Abstract: Medical processes combine medical actions which are performed by health care professionals while they observe signs and symptoms and decide about interventions, prescriptions, or tests, in order to deal with the health problem that affects a particular patient. Our research was centered in the representation of knowledge for the purpose of decision making in medical processes for chronic diseases. In order to achieve this objective, we followed three steps: (1) We performed an analysis and comparison of formal languages for procedural knowledge representation from a decision-making perspective. (2) We proposed an intuitive, easy, and effective mechanism of medical knowledge formalization. And, (3) we defined a methodology to model medical processes. Our new formalism to represent knowledge is called the extended Timed Transition Diagram (eTTD) and can be used to describe three basic levels of decision making in a long-term treatment: therapy strategy, dosage, and intolerances. The methodology can be applied manually to build eTTDs from clinical practice guidelines (CPGs) or automatically to construct them using the information available in clinical records about individual, multi-level medical processes. We validated eTTDs with clinical practice guidelines for arterial hypertension. The obtained models can be used as a baseline framework for medical, procedural decision support systems development.
    Thematic Areas: Interdisciplinar Information systems and management Engenharias iv Engenharias i Computer science, information systems Computer science, artificial intelligence Ciencias sociales Ciência da computação
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 0169023X
    Author's mail: david.riano@urv.cat
    Author identifier: 0000-0002-1608-0215
    Record's date: 2022-07-09
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S0169023X16303937?via%3Dihub
    Papper original source: Data & Knowledge Engineering. 119 36-57
    APA: Kamisalic, Aida; Riano, David; Kert, Suzana; Welzer, Tatjana; Zlatolas, Lili Nemec (2019). Multi-level medical knowledge formalization to support medical practice for chronic diseases. Data & Knowledge Engineering, 119(), 36-57. DOI: 10.1016/j.datak.2018.12.001
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1016/j.datak.2018.12.001
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2019
    Publication Type: Journal Publications
  • Keywords:

    Computer Science, Artificial Intelligence,Computer Science, Information Systems,Information Systems and Management
    Medical procedural knowledge
    Knowledge representation
    Decision support systems
    Decision making
    Interdisciplinar
    Information systems and management
    Engenharias iv
    Engenharias i
    Computer science, information systems
    Computer science, artificial intelligence
    Ciencias sociales
    Ciência da computação
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