Bio-Inspired Computing Algorithms in Dementia Diagnosis – An Application-Oriented Review

Abstract

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, Bio-motivated 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. This paper presents a comprehensive analysis of the different roles played by a biomotivated metaheuristics in the domain of dementia diagnosis with a detailed analysis of published work. The research status of biomotivated algorithms in dementia diagnosis is also analyzed. The results show that a biomotivated technique plays an important role in dementia diagnosis.

Note:
Funding declaration: This work is not supported fully or partially by any funding, organization, or agency.

Conflict of Interests: The authors declare that there is no conflict of interests regarding the publication of this paper.

Keywords: Dementia, Bio-motivated algorithms, Image segmentation, Meta-heuristic, optimization, Feature selection