Bio-inspired computing algorithms in dementia diagnosis – a application-oriented review

Dementia is a major neurocognitive disease which affects memory, thinking skills, attitudes, and social behavior, extremely causing disturbances in daily routine activities and social activities. Alzheimer is the most general form of dementia in the elderly. Recently, biomotivated techniques have become famous in the domain of healthcare and have obtained appreciable success. This review shows that these techniques are mostly utilized to resolve various problems such as image segmentation, feature selection, classification, and optimization in the detection of various disorders like cancer, anemia, Alzheimer, kidney and skin diseases. It is observed that the dementia diagnosis was performed using classical approaches which led to reduced performance (accuracy, precision). This performance parameter can be enhanced by using biomotivated techniques. This paper presents a comprehensive analysis of the different role of biomotivated metaheuristics in the domain of dementia diagnosis with a detailed analysis of published work. The results showed that a biomotivated technique plays an important role in dementia diagnosis.