Diagnosis‐Based Hybridization of Multimedical Tests and Sociodemographic Characteristics of Autism Spectrum Disorder Using Artificial Intelligence and Machine …

ME Alqaysi, AS Albahri… - International Journal of …, 2022 - Wiley Online Library
Autism spectrum disorder (ASD) is a complex neurobehavioral condition that begins in
childhood and continues throughout life, affecting communication and verbal and behavioral …

Artificial intelligence and internet of things in screening and management of autism spectrum disorder

T Ghosh, MH Al Banna, MS Rahman, MS Kaiser… - Sustainable Cities and …, 2021 - Elsevier
Autism is a disability that obstructs the process of a person's development. Autistic
individuals find it extremely difficult to cope with the world's pace, can not communicate …

Towards physician's experience: Development of machine learning model for the diagnosis of autism spectrum disorders based on complex T‐spherical fuzzy …

AS Albahri, AA Zaidan, HA AlSattar… - Computational …, 2023 - Wiley Online Library
Autism spectrum disorders (ASD) are a diverse group of conditions characterized by
difficulty with social interaction and communication. ASD is expected to be a high‐risk …

[HTML][HTML] Intelligent triage method for early diagnosis autism spectrum disorder (ASD) based on integrated fuzzy multi-criteria decision-making methods

SS Joudar, AS Albahri, RA Hamid - Informatics in Medicine Unlocked, 2023 - Elsevier
Background Autism spectrum disorder (ASD) symptoms and severity levels vary from patient
to patient, so treatment and healthcare will vary. However, little attention has been given to …

Early automated prediction model for the diagnosis and detection of children with autism spectrum disorders based on effective sociodemographic and family …

AS Albahri, RA Hamid, AA Zaidan… - Neural Computing and …, 2023 - Springer
Children with autism spectrum disorders (ASDs) tremendously impact people's lives, and the
incidence and prevalence of ASDs are increasing globally. Global health organisations and …

Hybrid Diagnosis Models for Autism Patients Based on Medical and Sociodemographic Features Using Machine Learning and Multicriteria Decision‐Making (MCDM) …

ME Alqaysi, AS Albahri… - … and Mathematical Methods …, 2022 - Wiley Online Library
Background and Contexts. Autism spectrum disorder (ASD) is difficult to diagnose,
prompting researchers to increase their efforts to find the best diagnosis by introducing …

Evaluation and benchmarking of hybrid machine learning models for autism spectrum disorder diagnosis using a 2-tuple linguistic neutrosophic fuzzy sets-based …

ME Alqaysi, AS Albahri, RA Hamid - Neural Computing and Applications, 2024 - Springer
Autism spectrum disorder (ASD) presents challenges for accurate diagnosis, prompting
researchers to search for an optimal diagnostic process. Feature selection (FS) approaches …

Improved machine learning based classification model for early autism detection

T Akter, MI Khan, MH Ali, MS Satu… - … Electrical and Signal …, 2021 - ieeexplore.ieee.org
Autism spectrum disorder is a complex, lifelong developmental disability where the affected
people show repetitive behavior and faces abnormal communication challenges. The goal …

A systematic review on prognosis of autism using machine learning techniques

M Malviya, J Chandra - ECS Transactions, 2022 - iopscience.iop.org
Quality of life (QoL) and QoL predictors have become crucial in the pandemic. Neurological
anomalies are at the highest level of QoL threats. Autism is a multisystem disorder that …

Predicting autism spectrum disorder (ASD) for toddlers and children using data mining techniques

RA Musa, ME Manaa… - Journal of Physics …, 2021 - iopscience.iop.org
Abstract Autism Spectrum Disorder (ASD) is a contemporary disease that has recently
spread among toddlers and children. Many researchers have been interested to determine …