Machine learning in autistic spectrum disorder behavioral research: A review and ways forward

F Thabtah - Informatics for Health and Social Care, 2019 - Taylor & Francis
ABSTRACT Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of
linguistic, communication, cognitive, and social skills and abilities. Despite being diagnosed …

An accessible and efficient autism screening method for behavioural data and predictive analyses

F Thabtah - Health informatics journal, 2019 - journals.sagepub.com
Autism spectrum disorder is associated with significant healthcare costs, and early diagnosis
can substantially reduce these. Unfortunately, waiting times for an autism spectrum disorder …

[HTML][HTML] A machine learning framework for sport result prediction

RP Bunker, F Thabtah - Applied computing and informatics, 2019 - Elsevier
Abstract Machine learning (ML) is one of the intelligent methodologies that have shown
promising results in the domains of classification and prediction. One of the expanding areas …

A new machine learning model based on induction of rules for autism detection

F Thabtah, D Peebles - Health informatics journal, 2020 - journals.sagepub.com
Autism spectrum disorder is a developmental disorder that describes certain challenges
associated with communication (verbal and non-verbal), social skills, and repetitive …

Autism spectrum disorder screening: machine learning adaptation and DSM-5 fulfillment

F Thabtah - Proceedings of the 1st International Conference on …, 2017 - dl.acm.org
One of the primary psychiatric disorders is Autistic Spectrum Disorder (ASD). ASD is a
mental disorder that limits the use of linguistic, communicative, cognitive, skills as well as …

A new computational intelligence approach to detect autistic features for autism screening

F Thabtah, F Kamalov, K Rajab - International journal of medical informatics, 2018 - Elsevier
Abstract Autism Spectrum Disorder (ASD) is one of the fastest growing developmental
disability diagnosis. General practitioners (GPs) and family physicians are typically the first …

Prediction of coronary heart disease using machine learning: an experimental analysis

AH Gonsalves, F Thabtah, RMA Mohammad… - proceedings of the 2019 …, 2019 - dl.acm.org
The field of medical analysis is often referred to be a valuable source of rich information.
Coronary Heart Disease (CHD) is one of the major causes of death all around the world …

A recent review of conventional vs. automated cybersecurity anti-phishing techniques

I Qabajeh, F Thabtah, F Chiclana - Computer Science Review, 2018 - Elsevier
In the era of electronic and mobile commerce, massive numbers of financial transactions are
conducted online on daily basis, which created potential fraudulent opportunities. A common …

Phishing detection: A recent intelligent machine learning comparison based on models content and features

N Abdelhamid, F Thabtah… - 2017 IEEE international …, 2017 - ieeexplore.ieee.org
In the last decade, numerous fake websites have been developed on the World Wide Web to
mimic trusted websites, with the aim of stealing financial assets from users and …

Software defect prediction based on correlation weighted class association rule mining

Y Shao, B Liu, S Wang, G Li - Knowledge-Based Systems, 2020 - Elsevier
Software defect prediction based on supervised learning plays a crucial role in guiding
software testing for resource allocation. In particular, it is worth noticing that using …