A Fuzzy Logic-Based Decision Support System for Early Detection of COVID-19: A Review and Comparative Analysis
DOI:
https://doi.org/10.70454/IJMRE.2025.50201Keywords:
Fuzzy logic, artificial intelligence, medical decision-making, expert systems, COVID-19 diagnosisAbstract
The global COVID-19 pandemic, resulting from the infection by the SARS-CoV-2 virus, is emphasizing the urgent need for rapid and accurate diagnostic methods for the control of the infection spread. Lab-based testing methods can take time, leading to diagnostic delays and a high risk of transmission. Fuzzy Logic-Based Expert System in Early Detection of COVID-19 Symptoms and Risk Assessment in Real-Time. We provide a systematic review of published fuzzy logic models for the COVID-19 diagnosis along with details of their methodologies, accuracy, and clinical usability. Results support that fuzzy logic systems improve diagnostic efficiency, lessen healthcare pathways, and enable decision-making in a timely manner.
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