Autism Spectrum Disorder Prediction Using Machine Learning and Design Science
Journal Title: International Journal of Experimental Research and Review - Year 2024, Vol 39, Issue 3
Abstract
Machine learning, a subset of Artificial Intelligence, has gained much recognition in facilitating disease prediction and the decision-making process in healthcare. One of the most often diagnosed developmental disorders in the world is Autism Spectrum Disorder (ASD). Around the world, it is reported to afflict 75 million people and the number of cases has gradually increased since studies began in the 1960s. The symptoms generally include communication deficits, sensory processing differences, and repetitive actions or behaviors. This research develops a model to detect ASD using Principal Component Analysis and Machine Learning algorithms to classify and predict the risk of ASD among pregnant women. Data was collected from National Hospital in Abuja, Nigeria. According to the results, PCA and Random Forest produced the best accuracy of 98.7%. Bayesian probability was employed to evaluate and verify the reliability of the model. The created model can aid doctors in diagnosing ASD.
Authors and Affiliations
Rajesh Prasad, Farida Musa, Hadiza Muhammad Ahmad, Santosh Kumar Upadhyay,Birendra Kumar Sharma
Keywords
Related Articles
- EP ID EP736000
- DOI 10.52756/ijerr.2024.v39spl.017
- Views 34
- Downloads 0
DNA and life cycle in Drosophila melanogaster: a nutritional-molecular connection
Nutrition plays a key role in different organisms to carry out life processes at different phases of life cycle. Furthermore, specific types of food are needed to build DNA. They are further required to synthesize genes/...
Performance Analysis of Millimeter-Wave Propagation Characteristics for Various Channel Models in the Indoor Environment
Due to the recent surge in the proliferation of smart wireless devices that feature higher data speeds, there has been a rise in demand for faster indoor data communication services. Moreover, there is a sharp increase i...
Development and validation of RP-HPLC method for simultaneous estimation of Ertugliflozin and Sitagliptin in bulk drug and tablet dosage form
To treat type 2 diabetes, in a combined tablet dosage form the ertugliflozin and sitagliptin were administered. Considering the less complication and readily availability of HPLC, the main objective of present study was...
Adulticidal and repellent properties of indigenous plant extracts against Larvae of mosquito: A Review
One method of prevention of mosquito borne diseases is the reduction of the mosquito population in the various stages of development, such as the use of ovicidal, larvicidal, pupicidal, adulticidal, and mosquitocidal sub...
A comparative physico-chemical, phytochemical and spectroscopic analysis of two medicinal plants belongs to Euphorbiaceae family: Acalypha indica L. and Euphorbia hirta L. growing in Paschim Medinipur District, West Bengal, India
Plants belong to Euphorbiaceae family, bearing enormous Medicinal potential due to the presence of various pharmacologically important secondary metabolites. Now a days, with the help of various tools and techniques like...