The role of intelligent technologies in early detection of autism spectrum disorder (asd): A sco** review

M Kohli, AK Kar, S Sinha - IEEE Access, 2022‏ - ieeexplore.ieee.org
Background: Two-year delay is reported between the first developmental concern raised by
the parents and the diagnosis of ASD (Autism Spectrum Disorder), delaying the start of early …

Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of the Italian Research Community

A Bottrighi, M Pennisi - Information, 2023‏ - mdpi.com
Artificial intelligence (AI) is becoming increasingly important, especially in the medical field.
While AI has been used in medicine for some time, its growth in the last decade is …

[HTML][HTML] Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism

C Allison, FE Matthews, L Ruta, G Pasco… - BMJ paediatrics …, 2021‏ - ncbi.nlm.nih.gov
Original research: Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population
screening study with follow-up: the case for multiple time-point screening for autism - PMC Back …

Towards autism subtype detection through identification of discriminatory factors using machine learning

T Akter, MH Ali, MS Satu, MI Khan… - … Conference on Brain …, 2021‏ - Springer
Autism spectrum disorder (ASD) is a neuro-developmental disease that has a lifetime impact
on a person's ability to interact and communicate with others. Early discovery of autism can …

Attention-Focused Eye Gaze Analysis to Predict Autistic Traits Using Transfer Learning

R Vasant Bidwe, S Mishra, S Kamini Bajaj… - International Journal of …, 2024‏ - Springer
Autism spectrum disorder (ASD) is a complex developmental issue that affects the behavior
and communication abilities of children. It is extremely needed to perceive it at an early age …

Machine learning-based brief version of the Caregiver-Teacher Report Form for preschoolers

GH Lin, SC Lee, YT Yu, CY Huang - Research in Developmental …, 2023‏ - Elsevier
Abstract Background The Caregiver-Teacher Report Form of the Child Behavior Checklist
for Ages 1½–5 (C-TRF) is a widely used checklist to identify emotional and behavioral …

[HTML][HTML] Modified meta heuristic BAT with ML classifiers for detection of autism spectrum disorder

M Sha, A Alqahtani, S Alsubai, AK Dutta - Biomolecules, 2023‏ - mdpi.com
ASD (autism spectrum disorder) is a complex developmental and neurological disorder that
impacts the social life of the affected person by disturbing their capability for interaction and …

A machine learning model based on CHAT-23 for early screening of autism in Chinese children

H Lu, H Zhang, Y Zhong, XY Meng, MF Zhang… - Frontiers in …, 2024‏ - frontiersin.org
Introduction Autism spectrum disorder (ASD) is a neurodevelopmental condition that
significantly impacts the mental, emotional, and social development of children. Early …

[HTML][HTML] Develo** a simplified measure to predict the risk of autism spectrum disorders: Abbreviating the M-CHAT-R using a machine learning approach in China

N Pan, L Chen, B Wu, F Chen, J Chen, S Huang… - Psychiatry …, 2025‏ - Elsevier
Background Early screening for autism spectrum disorder (ASD) is crucial, yet current
assessment tools in Chinese primary child care are limited in efficacy. Objective This study …

Sleep related rhythmic movement disorder: phenotypic characteristics and treatment response in a paediatric cohort

H Joels, A Benny, A Sharpe, B Postigo, B Joseph… - Sleep Medicine, 2023‏ - Elsevier
Objective To describe phenotypic, polysomnographic characteristics, impact, and treatment
response in children with sleep related rhythmic movement disorder (SR-RMD). Background …