Applications of supervised machine learning in autism spectrum disorder research: a review
Autism spectrum disorder (ASD) research has yet to leverage “big data” on the same scale
as other fields; however, advancements in easy, affordable data collection and analysis may …
as other fields; however, advancements in easy, affordable data collection and analysis may …
Machine learning for genetic prediction of psychiatric disorders: a systematic review
Abstract Machine learning methods have been employed to make predictions in psychiatry
from genotypes, with the potential to bring improved prediction of outcomes in psychiatric …
from genotypes, with the potential to bring improved prediction of outcomes in psychiatric …
[HTML][HTML] Patient similarity networks for precision medicine
Clinical research and practice in the 21st century is poised to be transformed by analysis of
computable electronic medical records and population-level genome-scale patient profiles …
computable electronic medical records and population-level genome-scale patient profiles …
[HTML][HTML] The use of artificial intelligence in screening and diagnosis of autism spectrum disorder: a literature review
Objectives: The detection of autism spectrum disorder (ASD) is based on behavioral
observations. To build a more objective datadriven method for screening and diagnosing …
observations. To build a more objective datadriven method for screening and diagnosing …
Machine learning-based blood RNA signature for diagnosis of autism spectrum disorder
Early diagnosis of autism spectrum disorder (ASD) is crucial for providing appropriate
treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy …
treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy …
Uncovering obsessive-compulsive disorder risk genes in a pediatric cohort by high-resolution analysis of copy number variation
MJ Gazzellone, M Zarrei, CL Burton, S Walker… - Journal of …, 2016 - Springer
Background Obsessive-compulsive disorder (OCD) is a heterogeneous neuropsychiatric
condition, thought to have a significant genetic component. When onset occurs in childhood …
condition, thought to have a significant genetic component. When onset occurs in childhood …
Whole-genome sequencing suggests schizophrenia risk mechanisms in humans with 22q11. 2 deletion syndrome
Abstract Chromosome 22q11. 2 microdeletions impart a high but incomplete risk for
schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 …
schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 …
MicroRNA dysregulation, gene networks, and risk for schizophrenia in 22q11. 2 deletion syndrome
The role of microRNAs (miRNAs) in the etiology of schizophrenia is increasingly recognized.
Microdeletions at chromosome 22q11. 2 are recurrent structural variants that impart a high …
Microdeletions at chromosome 22q11. 2 are recurrent structural variants that impart a high …
High-resolution SNP genotyping platform identified recurrent and novel CNVs in autism multiplex families
Single nucleotide polymorphisms (SNPs)-based genotyping using microarray platform is
now frequently used to detect copy number variants (CNVs) in the human genome. Here, we …
now frequently used to detect copy number variants (CNVs) in the human genome. Here, we …
A Systematic Review of Genetics-and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis
The process of identification and management of neurological disorder conditions faces
challenges, prompting the investigation of novel methods in order to improve diagnostic …
challenges, prompting the investigation of novel methods in order to improve diagnostic …