In many domains of our daily life (eg, agriculture, forestry, health, etc.), both laymen and
experts need to classify entities into two binary classes (yes/no, good/bad …

In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-
Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton …

Chronic kidney disease (CKD) is a widespread illness affecting humans globally. It poses a
significant challenge for societies and global health care systems. Specialized screening …

One of the main challenges in breast cancer risk assessment is to provide a patient with an
easily interpretable perspective on her disease's situation. This paper proposes a new …

An essential aspect of healthcare is receiving an appropriate and opportune disease
diagnosis. In recent years, there has been enormous progress in combining artificial …

Diabetic retinopathy (DR) is one of the worse conditions caused by diabetes mellitus (DM).
DR can leave the patient completely blind because it may have no symptoms in its initial …

Hybridization of metaheuristic algorithms has recently been introduced to increase the
search capabilities of a traditional metaheuristic algorithms. The fuzzy optimization approach …

Fuzzy matching techniques are the presently used methods in translating the words. Neural
machine translation and statistical machine translation are the methods used in MT. In …

Despite the rapid development of the automated fingerprint identification system, some
challenging fields need more enhancement. Typically, fingerprints suffer from distortion …

In this paper, we present a multilevel fuzzy inference model for predicting the risk of type 2
diabetes. We have designed a system for predicting this risk by taking into account various …