[PDF][PDF] Modern views of machine learning for precision psychiatry
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …
the advent of functional neuroimaging, novel technologies and methods provide new …
Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
[HTML][HTML] A multimodal machine learning system in early screening for toddlers with autism spectrum disorders based on the response to name
Background Reduced or absence of the response to name (RTN) has been widely reported
as an early specific indicator for autism spectrum disorder (ASD), while few studies have …
as an early specific indicator for autism spectrum disorder (ASD), while few studies have …
[HTML][HTML] Supervised machine learning: A new method to predict the outcomes following exercise intervention in children with autism spectrum disorder
Z Sun, Y Yuan, X Dong, Z Liu, K Cai, W Cheng… - International Journal of …, 2023 - Elsevier
The individual differences among children with autism spectrum disorder (ASD) may make it
challenging to achieve comparable benefits from a specific exercise intervention program. A …
challenging to achieve comparable benefits from a specific exercise intervention program. A …
EEG-based major depressive disorder recognition by selecting discriminative features via stochastic search
Objective. Major depressive disorder (MDD) is a prevalent psychiatric disorder whose
diagnosis relies on experienced psychiatrists, resulting in a low diagnosis rate. As a typical …
diagnosis relies on experienced psychiatrists, resulting in a low diagnosis rate. As a typical …
[HTML][HTML] Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study
Background: Depressive and manic episodes within bipolar disorder (BD) and major
depressive disorder (MDD) involve altered mood, sleep, and activity, alongside …
depressive disorder (MDD) involve altered mood, sleep, and activity, alongside …
Assessment of neuroanatomical endophenotypes of autism spectrum disorder and association with characteristics of individuals with schizophrenia and the general …
G Hwang, J Wen, S Sotardi, ES Brodkin… - JAMA …, 2023 - jamanetwork.com
Importance Autism spectrum disorder (ASD) is associated with significant clinical,
neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment …
neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment …
Symptom dimensions of resting-state electroencephalographic functional connectivity in autism
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized
by social and communication deficits (SCDs), restricted and repetitive behaviors (RRBs) and …
by social and communication deficits (SCDs), restricted and repetitive behaviors (RRBs) and …
Discovering the gene-brain-behavior link in autism via generative machine learning
S Kundu, H Sair, EH Sherr, P Mukherjee… - Science …, 2024 - science.org
Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first
approach could transform understanding and treatment of autism. However, isolating the …
approach could transform understanding and treatment of autism. However, isolating the …
[HTML][HTML] Unravelling individual rhythmic abilities using machine learning
Humans can easily extract the rhythm of a complex sound, like music, and move to its
regular beat, like in dance. These abilities are modulated by musical training and vary …
regular beat, like in dance. These abilities are modulated by musical training and vary …