Applications of machine learning methods to assist the diagnosis of autism spectrum disorder (2023)
Book Chapter
Elbattah, M., Carette, R., Cilia, F., Guérin, J., & Dequen, G. (2023). Applications of machine learning methods to assist the diagnosis of autism spectrum disorder. In Neural Engineering Techniques for Autism Spectrum Disorder, Volume 2: Diagnosis and Clinical Analysis (99-119). Elsevier. https://doi.org/10.1016/B978-0-12-824421-0.00013-8

Autism spectrum disorder (ASD) is a lifelong neuro-developmental disorder that is generally marked by a set of communication and social impairments. The early diagnosis of autism is genuinely beneficial for the welfare of children and parents as well... Read More about Applications of machine learning methods to assist the diagnosis of autism spectrum disorder.

Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA) (2022)
Book Chapter
Smith, B. J., Smith, A. D., & Dunn, E. C. (2022). Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA). In Sensitive Periods of Brain Development and Preventive Interventions (215-234). Springer. https://doi.org/10.1007/7854_2021_280

Sensitive periods are times during development when life experiences can have a greater impact on outcomes than at other periods during the life course. However, a dearth of sophisticated methods for studying time-dependent exposure-outcome relations... Read More about Statistical modeling of sensitive period effects using the structured life course modelling approach (SLCMA).