A review of and roadmap for data science and machine learning for the neuropsychiatric phenotype of autism

P Washington, DP Wall - Annual Review of Biomedical Data …, 2023 - annualreviews.org
Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44
children. Like many neurological disorder phenotypes, the diagnostic features are …

Multi-omics data integration methods and their applications in psychiatric disorders

A Sathyanarayanan, TT Mueller, MA Moni… - European …, 2023 - Elsevier
To study mental illness and health, in the past researchers have often broken down their
complexity into individual subsystems (eg, genomics, transcriptomics, proteomics, clinical …

Impacts of 5G Machine Learning Techniques on Telemedicine and Social Media Professional Connection in Healthcare

PSS Sreedhar, V Sujay, MR Rani, L Melita… - … Trends Using Social …, 2024 - igi-global.com
The healthcare industry is undergoing a transformation due to the convergence of advanced
technologies. This chapter explores the impact of 5G connectivity, machine learning, and …

[HTML][HTML] Classifying autism from crowdsourced semistructured speech recordings: machine learning model comparison study

NA Chi, P Washington, A Kline, A Husic… - JMIR pediatrics and …, 2022 - pediatrics.jmir.org
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder that results
in altered behavior, social development, and communication patterns. In recent years …

Annual Research Review: Translational machine learning for child and adolescent psychiatry

D Dwyer, N Koutsouleris - Journal of Child Psychology and …, 2022 - Wiley Online Library
Children and adolescents could benefit from the use of predictive tools that facilitate
personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been …

[HTML][HTML] The classification of abnormal hand movement to aid in autism detection: Machine learning study

A Lakkapragada, A Kline, OC Mutlu… - JMIR Biomedical …, 2022 - biomedeng.jmir.org
Background A formal autism diagnosis can be an inefficient and lengthy process. Families
may wait several months or longer before receiving a diagnosis for their child despite …

Activity recognition with moving cameras and few training examples: applications for detection of autism-related headbanging

P Washington, A Kline, OC Mutlu, E Leblanc… - Extended abstracts of …, 2021 - dl.acm.org
Activity recognition computer vision algorithms can be used to detect the presence of autism-
related behaviors, including what are termed “restricted and repetitive behaviors”, or …

[HTML][HTML] Training and profiling a pediatric facial expression classifier for children on mobile devices: machine learning study

A Banerjee, OC Mutlu, A Kline, S Surabhi… - JMIR formative …, 2023 - formative.jmir.org
Background Implementing automated facial expression recognition on mobile devices could
provide an accessible diagnostic and therapeutic tool for those who struggle to recognize …

Feature replacement methods enable reliable home video analysis for machine learning detection of autism

E Leblanc, P Washington, M Varma, K Dunlap… - Scientific reports, 2020 - nature.com
Abstract Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million
children worldwide and for which early diagnosis is critical to the outcome of behavior …

[HTML][HTML] Blockchain-based crowdsourced deep reinforcement learning as a service

A Alagha, H Otrok, S Singh, R Mizouni, J Bentahar - Information Sciences, 2024 - Elsevier
Abstract Deep Reinforcement Learning (DRL) has emerged as a powerful paradigm for
solving complex problems. However, its full potential remains inaccessible to a broader …