Using Machine Learning to Diagnose Autism Based on Eye Tracking Technology
<b>Background/Objectives:</b> One of the key challenges in autism is early diagnosis. Early diagnosis leads to early interventions that improve the condition and not worsen autism in the future. Currently, autism diagnoses are based on monitoring by a doctor or specialist after the child...
Saved in:
| Main Authors: | Ameera S. Jaradat, Mohammad Wedyan, Saja Alomari, Malek Mahmoud Barhoush |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/15/1/66 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Editorial: Improving autism spectrum disorder diagnosis using machine learning techniques
by: Mahmoud Elbattah, et al.
Published: (2024-12-01) -
A Study on Staging Cystic Echinococcosis Using Machine Learning Methods
by: Tuvshinsaikhan Tegshee, et al.
Published: (2025-02-01) -
Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks
by: Adoración Antolí, et al.
Published: (2025-06-01) -
Exploring pesticide risk in autism via integrative machine learning and network toxicology
by: Ling Qi, et al.
Published: (2025-06-01) -
Autism Prevalence Information And Diagnosis Processes In Cyprus, Greece And Malta
by: Petinou K, et al.
Published: (2024-12-01)