Autism Spectrum Disorder Prediction Using Machine Learning and Design Science

• DOI: 10.52756/ijerr.2024.v39spl.017
• Publication Date: 2024-06-01T18:46:37Z
• Authors: Rajesh Prasad; Farida Musa; Hadiza Muhammad A...; Santosh Kumar Upa...; Birendra Kumar Sh...

Machine learning, a subset of Artificial Intelligence, has gained much recognition in facilitating disease prediction and the decision-making process healthcare. One most often diagnosed developmental disorders world is Autism Spectrum Disorder (ASD). Around world, it reported to afflict 75 million people number cases gradually increased since studies began 1960s. The symptoms generally include communication deficits, sensory processing differences, repetitive actions or behaviors. This research develops model detect ASD using Principal Component Analysis Learning algorithms classify predict risk among pregnant women. Data was collected from National Hospital Abuja, Nigeria. According results, PCA Random Forest produced best accuracy 98.7%. Bayesian probability employed evaluate verify reliability model. created can aid doctors diagnosing ASD.