DOI - Mendel University Press

DOI identifiers

DOI: 10.11118/978-80-7701-042-9-0062

FUZZY LOGIC METHODOLOGICAL ANALYSIS OF DATA-DRIVEN DECISION MAKING AND ARTIFICIAL INTELLIGENCE MODELLING IN CLINICAL ENVIRONMENTS

Henriett Karolyi1, Antal Martzy1, Anna Dunay1
1 John von Neumann University, Doctoral School of Management and Business Administration, Budapest, Hungary

The creation and operation of data-driven decision support systems and artificial intelligence for clinical practice is a complex, innovative, rapidly evolving, multidisciplinary process. The effectiveness of existing systems also needs to be measured by a number of difficult-to-quantify parameters to ensure that the models are effective. The setting up of data-driven decision making and artificial intelligence models, the expectations of patients and physicians, the quantity and quality of the data analysed, the decision thresholds, the operational practices of users, all have a complex impact on patient and care safety and the reliability of decision support. Conscious and continuous development of models, complex testing, control of their biases, adaptation and verification in new areas, complex data asset management contribute to the practical effectiveness of models.

Keywords: data-driven decisionmaking, clinical, medical, thresholds

pages: 62-64, online: 2025



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