An Artificial Intelligence-Based Fuzzy Logic System for Periodontitis Risk Assessment in Patients with Type 2 Diabetes Mellitus
In our developed fuzzy system, BMI, G, C, and T as input data resulted in periodontitis risk estimation. PCRisk was correlated with nrPP: when PCRisk increased by 1.881 units, nrPP increased by 1 unit. The fuzzy logic-based system effectively estimated periodontitis risk in type 2 diabetes patients, showing a significant correlation with the number of periodontal pockets. These findings highlight its potential for early diagnosis and improved interdisciplinary care.
Authors
- Ioana Scrobotă (ORCID: https://orcid.org/0000-0002-2643-761X)
- Olivia Andreea Marcu (ORCID: https://orcid.org/0000-0001-6530-5700)
- Liliana Sachelarie (ORCID: https://orcid.org/0000-0001-7701-2307)
- Florin Blaga (ORCID: https://orcid.org/0000-0002-8300-1396)
- Ioana Duncea
- Gilda Mihaela Iova
- Silviu Valentin Vlad (ORCID: https://orcid.org/0009-0003-8633-6866)
Institutions
- University of Oradea (RO)
- Iuliu Hațieganu University of Medicine and Pharmacy (RO)
- Apollonia University (RO)
Publication Details
- Journal
- Bioengineering
- Published
- 2025-02-20
- DOI
- https://doi.org/10.3390/bioengineering12030211
- Citations
- 5
- Primary Topic
- Oral microbiology and periodontitis research
- Type
- article
- Field-Weighted Citation Impact
- 7.33