FEATURE SELECTION IN HEALTH CARE DOMAIN DATA USING QUICK REDUCT ALGORITHM FOR EARLY DETECTION OF AUTISM SPECTRUM DISORDER

  • J. A. Esther Rani et al.

Abstract

Autism Spectrum Disorder (ASD) is a severe developmental disorder that weakens the capacity to
communicate and interact. The number of toddlers affected by ASD has increased globally, hence the
operation of easy and accurate screening methods are a need of the hour. The screening method should
conclude whether the individual should go for formal clinical diagnosis or not. Early diagnosis helps
to reduce the cost spending on health care and saves from deterioration. Feature selection enables to
identify the best features from the given autism dataset which will eventually lead to autism spectrum
disorder. A measure is taken using Quick Reduct algorithm to find an earlier solution so that the
prevention or cure will be earlier. Currently, very few autism datasets related with clinical or screening
is only available. Hence this paper attempts to propose the probable behavioural factors which will
lead to Autism spectrum disorder for a given dataset

Published
2020-04-13