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predicting-autism-in-toddlers-through-machine-learning's Introduction

Predicting-Autism-in-Toddlers-through-Machine-Learning [Currently In Progress]

The Problem

Current screening processes incur costs and require expertise. Therefore, this project will apply ML to predict and screen autism in children using a simple set of parameters reducing the cost and expertise needed.

Useful Links

  • Article Link The article on provides information on the criteria for diagnosing autism spectrum disorder (ASD) according to the Diagn and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). In summary, the criteria includes persistent deficits in social communication and social interaction, restricted and repetitive patterns of behavior and interests, symptoms present in early developmental period, symptoms causing clinically significant impairment and not better explained by intellectual disability or global developmental delay. The article also provides additional information on changes in diagnostic criteria for ASD in the DSM-5 and resources for further information and support for individuals and families affected by ASD.

  • Article Link It describes the common characteristics of ASD, including problems with social communication and interaction, restricted or repetitive behaviors or interests, and other related characteristics such as delayed language skills, delayed movement skills, and hyperactive, impulsive and inattentive behaviour. It also mentions that not all children with ASD will have all or any of the listed behaviors

predicting-autism-in-toddlers-through-machine-learning's People

Contributors

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Stargazers

CHAKALI RAVINDRA avatar

Watchers

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Forkers

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