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 …
Comparison of the performance of machine learning-based algorithms for predicting depression and anxiety among University Students in Bangladesh: A result of the …
MIH Nayan, MSG Uddin, MI Hossain… - Asian Journal of …, 2022 - journals.lww.com
Methods: A structured questionnaire-based online survey was conducted on 2121 university
students (private and public) living in Bangladesh. After obtaining informed consent, the …
students (private and public) living in Bangladesh. After obtaining informed consent, the …
Machine learning based disease prediction from genotype data
Using results from genome-wide association studies for understanding complex traits is a
current challenge. Here we review how genotype data can be used with different machine …
current challenge. Here we review how genotype data can be used with different machine …
Introduction to machine learning
Abstract Machine learning is becoming increasingly popular in the neuroscientific literature.
However, navigating the literature can easily become overwhelming, especially for the …
However, navigating the literature can easily become overwhelming, especially for the …
Machine learning approaches for the prediction of obesity using publicly available genetic profiles
This paper presents a novel approach based on the analysis of genetic variants from
publicly available genetic profiles and the manually curated database, the National Human …
publicly available genetic profiles and the manually curated database, the National Human …
A pattern of cognitive deficits stratified for genetic and environmental risk reliably classifies patients with schizophrenia from healthy control subjects
Background Schizophrenia risk is associated with both genetic and environmental risk
factors. Furthermore, cognitive abnormalities are established core characteristics of …
factors. Furthermore, cognitive abnormalities are established core characteristics of …
Multi-modal deep learning from imaging genomic data for schizophrenia classification
Background Schizophrenia (SZ) is a psychiatric condition that adversely affects an
individual's cognitive, emotional, and behavioral aspects. The etiology of SZ, although …
individual's cognitive, emotional, and behavioral aspects. The etiology of SZ, although …
Deep Learning based techniques for Neuro-degenerative disorders detection
Mental disorders are neural issues that influence brain cognition and social connectivity.
The significant increase in mental disorders needs prompt detection for effective treatment …
The significant increase in mental disorders needs prompt detection for effective treatment …
Prediction of transition to psychosis from an at-risk mental state using structural neuroimaging, genetic, and environmental data
Introduction Psychosis is usually preceded by a prodromal phase in which patients are
clinically identified as being at in an “At Risk Mental State”(ARMS). A few studies have …
clinically identified as being at in an “At Risk Mental State”(ARMS). A few studies have …
[HTML][HTML] Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review
V Gashkarimov, R Sultanova, I Efremov… - Consortium …, 2023 - cyberleninka.ru
BACKGROUND: Schizophrenia is a severe psychiatric disorder associated with a significant
negative impact. Early diagnosis and treatment of schizophrenia has a favorable effect on …
negative impact. Early diagnosis and treatment of schizophrenia has a favorable effect on …