Articles producció científica> Medicina i Cirurgia

HTE 3.0: Knowledge-based systems in cascade for familial hypercholesterolemia detection and dyslipidemia treatment

  • Identification data

    Identifier: imarina:9229548
    Authors:
    Lopez, BeatrizTorrent-Fontbona, FerranMasana Marin, LuisZamora, Alberto
    Abstract:
    HTE 3.0 aims to support clinicians in the detection of patients with dyslipidemia, especially patients with familial hypercholesterolemia (FH), and in the recommendation of personalized lipid-lowering treatments. The core of HTE 3.0 is a clinical decision support system in which several knowledge-based systems are serialized: patient detection, therapeutic target setting, personalized treatment assessment, and treatment combination and prioritization, according to different criteria. The experimental evaluation of HTE 3.0 shows that the use of HTE 3.0 would mean increasing the capacity to detect FH by 5.7 times compared with usual clinical practice. Regarding the lipid-lowering treatment, a comparison of 18 cases among seven lipidologists shows that the differences between treatments provided by HTE 3.0 and human lipidologists are smaller than the differences between human experts.
  • Others:

    Author, as appears in the article.: Lopez, Beatriz; Torrent-Fontbona, Ferran; Masana Marin, Luis; Zamora, Alberto;
    Department: Medicina i Cirurgia
    URV's Author/s: Masana Marín, Luis
    Keywords: Tool Risk Medication Lowering treatment Knowledge-based systems Hypercholesterolemia detection Guideline Efficacy Dyslipidemia treatment Disease Decision-support-system Clinical decision support systems Cholesterol management
    Abstract: HTE 3.0 aims to support clinicians in the detection of patients with dyslipidemia, especially patients with familial hypercholesterolemia (FH), and in the recommendation of personalized lipid-lowering treatments. The core of HTE 3.0 is a clinical decision support system in which several knowledge-based systems are serialized: patient detection, therapeutic target setting, personalized treatment assessment, and treatment combination and prioritization, according to different criteria. The experimental evaluation of HTE 3.0 shows that the use of HTE 3.0 would mean increasing the capacity to detect FH by 5.7 times compared with usual clinical practice. Regarding the lipid-lowering treatment, a comparison of 18 cases among seven lipidologists shows that the differences between treatments provided by HTE 3.0 and human lipidologists are smaller than the differences between human experts.
    Thematic Areas: Theoretical computer science Engenharias iii Control and systems engineering Computer science, theory & methods Computer science, artificial intelligence Computational theory and mathematics Ciência da computação Artificial intelligence Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: luis.masana@urv.cat
    Author identifier: 0000-0002-0789-4954
    Record's date: 2024-09-07
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://onlinelibrary.wiley.com/doi/full/10.1111/exsy.12835
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Expert Systems. 39 (1):
    APA: Lopez, Beatriz; Torrent-Fontbona, Ferran; Masana Marin, Luis; Zamora, Alberto; (2022). HTE 3.0: Knowledge-based systems in cascade for familial hypercholesterolemia detection and dyslipidemia treatment. Expert Systems, 39(1), -. DOI: 10.1111/exsy.12835
    Article's DOI: 10.1111/exsy.12835
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Artificial Intelligence,Computational Theory and Mathematics,Computer Science, Artificial Intelligence,Computer Science, Theory & Methods,Control and Systems Engineering,Theoretical Computer Science
    Tool
    Risk
    Medication
    Lowering treatment
    Knowledge-based systems
    Hypercholesterolemia detection
    Guideline
    Efficacy
    Dyslipidemia treatment
    Disease
    Decision-support-system
    Clinical decision support systems
    Cholesterol management
    Theoretical computer science
    Engenharias iii
    Control and systems engineering
    Computer science, theory & methods
    Computer science, artificial intelligence
    Computational theory and mathematics
    Ciência da computação
    Artificial intelligence
    Administração pública e de empresas, ciências contábeis e turismo
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