scholarly journals Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey

2021 ◽  
Vol 14 ◽  
Author(s):  
Taban Eslami ◽  
Fahad Almuqhim ◽  
Joseph S. Raiker ◽  
Fahad Saeed
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Imaging Techniques ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Hyperactivity Disorder ◽  
Machine Learning Model

Here we summarize recent progress in machine learning model for diagnosis of Autism Spectrum Disorder (ASD) and Attention-deficit/Hyperactivity Disorder (ADHD). We outline and describe the machine-learning, especially deep-learning, techniques that are suitable for addressing research questions in this domain, pitfalls of the available methods, as well as future directions for the field. We envision a future where the diagnosis of ASD, ADHD, and other mental disorders is accomplished, and quantified using imaging techniques, such as MRI, and machine-learning models.

scholarly journals Surface-based shared and distinct resting functional connectivity in attention-deficit hyperactivity disorder and autism spectrum disorder

2018 ◽  
Vol 214 (06) ◽  
pp. 339-344 ◽  
Author(s):  
Minyoung Jung ◽  
Yiheng Tu ◽  
Joel Park ◽  
Kristen Jorgenson ◽  
Courtney Lang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Autism Spectrum ◽  
Diagnostic Methods ◽  
Spectrum Disorder ◽  
Typical Development ◽  
Hyperactivity Disorder

BackgroundBoth attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental disorders with a high prevalence. They are often comorbid and both exhibit abnormalities in sustained attention, yet common and distinct neural patterns of ASD and ADHD remain unidentified.AimsTo investigate shared and distinct functional connectivity patterns in a relatively large sample of boys (7- to 15-year-olds) with ADHD, ASD and typical development matched by age, gender and IQ.MethodWe applied machine learning techniques to investigate patterns of surface-based brain resting-state connectivity in 86 boys with ASD, 83 boys with ADHD and 125 boys with typical development.ResultsWe observed increased functional connectivity within the limbic and somatomotor networks in boys with ASD compared with boys with typical development. We also observed increased functional connectivity within the limbic, visual, default mode, somatomotor, dorsal attention, frontoparietal and ventral attention networks in boys with ADHD compared with boys with ASD. In addition, using a machine learning approach, we were able to discriminate typical development from ASD, typical development from ADHD and ASD from ADHD with accuracy rates of 76.3%, 84.1%, and 79.3%, respectively.ConclusionsOur results may shed new light on the underlying mechanisms of ASD and ADHD and facilitate the development of new diagnostic methods for these disorders.Declaration of interestJ.K. holds equity in a startup company, MNT.

Attention Deficit Hyperactivity Disorder in Autism Spectrum Disorder

2020 ◽  
pp. 158-176
Author(s):  
Karen Bearss ◽  
Aaron J. Kaat
Keyword(s):  
Autism Spectrum Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Autism Spectrum ◽  
Developmental Trajectory ◽  
Spectrum Disorder ◽  
Adhd Symptoms ◽  
Functional Impairments ◽  
Hyperactivity Disorder ◽  
Delayed Recognition

This chapter will review the available evidence on individuals with co-occurring diagnoses of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). This chapter contends that children diagnosed with both disorders (ASD+ADHD) are a subset of the ASD population that is at risk for delayed recognition of their ASD diagnosis, poor treatment response, and poorer functional outcomes compared to those with ASD without ADHD. Specifically, the chapter highlights the best estimates of the prevalence of the comorbidity, the developmental trajectory of people with co-occurring ASD and ADHD, how ADHD symptoms change across development, overlapping genetic and neurobiological risk factors, psychometrics of ADHD diagnostic instruments in an ASD population, neuropsychological and functional impairments associated with co-occurring ASD and ADHD, and the current state of evidence-based treatment for both ASD and ADHD symptoms. Finally, the chapter discusses fruitful avenues of research for improving understanding of this high-risk comorbidity so that mechanism-to-treatment pathways for ADHD in children with ASD can be better developed.

scholarly journals Medications for attention-deficit/hyperactivity disorder in individuals with or without coexisting autism spectrum disorder: analysis of data from the Swedish prescribed drug register

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Viktoria Johansson ◽  
Sven Sandin ◽  
Zheng Chang ◽  
Mark J. Taylor ◽  
Paul Lichtenstein ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Clinical Studies ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Prescribing Patterns ◽  
Adhd Medication ◽  
Hyperactivity Disorder ◽  
Drug Register

Abstract Background Clinical studies found that medication for attention-deficit/hyperactivity disorder (ADHD) is effective in coexisting autism spectrum disorder (ASD), but current research is based on small clinical studies mainly performed on children or adolescents. We here use register data to examine if individuals with ADHD and coexisting ASD present differences in the prescribing patterns of ADHD medication when compared to individuals with pure ADHD. Methods Data with information on filled prescriptions and diagnoses was retrieved from the Swedish Prescribed Drug Register and the National Patient Register. We identified 34,374 individuals with pure ADHD and 5012 individuals with ADHD and coexisting ASD, aged between 3 and 80 years. The first treatment episode with ADHD medications (≥ 2 filled prescriptions within 90 days) and daily doses of methylphenidate during a 3-year period was measured. Odds ratios (ORs) were calculated for the likelihood of being prescribed ADHD medication in individuals with and without ASD and Wilcoxon rank-sum test was used to compare group differences in dose per day. Results Individuals with ADHD and coexisting ASD were less likely to start continuous treatment with ADHD medication (ADHD 80.5%; ADHD with ASD 76.2%; OR, 0.80; 95% confidence interval, 0.75-0.86), were less likely to be prescribed methylphenidate, and were more commonly prescribed second line treatments such as dexamphetamine, amphetamine, or modafinil. No group difference was observed for atomoxetine. In adults with ADHD and coexisting ASD, methylphenidate was prescribed in lower daily doses over three years as compared to individuals with pure ADHD. Conclusions The findings indicate that there are differences in the medical treatment of individuals with or without ASD. If these differences are due to different medication responses in ASD or due to other factors such as clinicians’ perceptions of medication effects in patients with ASD, needs to be further studied.

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