ASD is a neurological disorder that affects over 1 in 44 chilren and this rate has increased. The diagnosis process can be timely and costly. This will make it difficult for the patients to adhere to the prescribed treatments and will hinder the progress of the patient. This project is focused on increasing the efficiency of this diagnosis process through machine learning techniques. The proposed datasets are; ASD Screening Data for Adult, ASD screening Data for Children and ASD Screening Data for Adolescent. These datasets are a categorical, continuous, and binary data type. They have 21 common attributes and a total of 1,100 instances.
Professional Studies (MS)
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Graduate Programs & Research (Dubai)
Alfalasi, Mahra Musabbah Bin Beyat, "Early detection of autism spectrum disorder (ASD) using Machine Learning techniques" (2023). Thesis. Rochester Institute of Technology. Accessed from