Ten quick tips for fuzzy logic modeling of biomedical systems

Davide Chicco (Corresponding author), Simone Spolaor, Marco S. Nobile

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
8 Downloads (Pure)

Abstract

Fuzzy logic is useful tool to describe and represent biological or medical scenarios, where often states and outcomes are not only completely true or completely false, but rather partially true or partially false. Despite its usefulness and spread, fuzzy logic modeling might easily be done in the wrong way, especially by beginners and unexperienced researchers, who might overlook some important aspects or might make common mistakes. Malpractices and pitfalls, in turn, can lead to wrong or overoptimistic, inflated results, with negative consequences to the biomedical research community trying to comprehend a particular phenomenon, or even to patients suffering from the investigated disease. To avoid common mistakes, we present here a list of quick tips for fuzzy logic modeling any biomedical scenario: some guidelines which should be taken into account by any fuzzy logic practitioner, including experts. We believe our best practices can have a strong impact in the scientific community, allowing researchers who follow them to obtain better, more reliable results and outcomes in biomedical contexts.

Original languageEnglish
Article numbere1011700
Number of pages12
JournalPLoS Computational Biology
Volume19
Issue number12
DOIs
Publication statusPublished - Dec 2023

Bibliographical note

Copyright: © 2023 Chicco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding

The work of D.C. was funded by the European Union – Next Generation EU programme, in the context of The National Recovery and Resilience Plan, Investment Partenariato Esteso PE8 “Conseguenze e sfide dell’invecchiamento”, Project Age-It (Ageing Well in an Ageing Society) and was also partially supported by Ministero dell’Università e della Ricerca of Italy under the “Dipartimenti di Eccellenza 2023-2027” ReGAInS grant assigned to Dipartimento di Informatica Sistemistica e Comunicazione at Università di Milano-Bicocca. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

FundersFunder number
Università di Milano-Bicocca
European Commission
Ministero dell'Università e della Ricerca

    Keywords

    • Humans
    • Fuzzy Logic

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