Machine learning approaches and applications in genome wide association study for Alzheimer's disease: A systematic review
Machine learning algorithms have been used for detection (and possibly) prediction of
Alzheimer's disease using genotype information, with the potential to enhance the outcome …
Alzheimer's disease using genotype information, with the potential to enhance the outcome …
[PDF][PDF] In-Silico Identification of Single Nucleotide Polymorphisms (SNPs) Associated with Alzheimer's Disease
APM Aljamali - pedia.svuonline.org
Background: With the increase in the aging population, the risk of agerelated conditions
such as AD has also grown. With AD being the most common neurodegenerative disease …
such as AD has also grown. With AD being the most common neurodegenerative disease …
Predicting the disease of Alzheimer (AD) with SNP biomarkers and clinical data based decision support system using data mining classification approaches
O Erdoğan - 2012 - open.metu.edu.tr
Single Nucleotide Polymorphisms (SNPs) are the most common DNA sequence variations
where only a single nucleotide (A, T, C, G) in the human genome differs between …
where only a single nucleotide (A, T, C, G) in the human genome differs between …
Developing an early predictive system for identifying genetic biomarkers associated to Alzheimer's disease using machine learning techniques
MM Abd El Hamid, MS Mabrouk… - … : Applications, Basis and …, 2019 - World Scientific
Alzheimer's disease (AD) is an irreversible, progressive disorder that assaults the nerve
cells of the brain. It is the most widely recognized kind of dementia among older adults …
cells of the brain. It is the most widely recognized kind of dementia among older adults …
Identification of Alzheimer's disease-related genes based on data integration method
Alzheimer disease (AD) is the fourth major cause of death in the elderly following cancer,
heart disease and cerebrovascular disease. Finding candidate causal genes can help in the …
heart disease and cerebrovascular disease. Finding candidate causal genes can help in the …
Prioritization of risk genes for Alzheimer's disease: an analysis framework using spatial and temporal gene expression data in the human brain based on support …
S Wang, X Fang, X Wen, C Yang, Y Yang… - Frontiers in …, 2023 - frontiersin.org
Background: Alzheimer's disease (AD) is a complex disorder, and its risk is influenced by
multiple genetic and environmental factors. In this study, an AD risk gene prediction …
multiple genetic and environmental factors. In this study, an AD risk gene prediction …
Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree
O Erdoğan, Y Aydin Son - e-Health–For Continuity of Care, 2014 - ebooks.iospress.nl
Abstract Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations
where only a single nucleotide differs between individuals. Individual SNPs and SNP …
where only a single nucleotide differs between individuals. Individual SNPs and SNP …
[HTML][HTML] The application of artificial intelligence in the genetic study of Alzheimer's disease
R Mishra, B Li - Aging and disease, 2020 - ncbi.nlm.nih.gov
Alzheimer's disease (AD) is a neurodegenerative disease in which genetic factors contribute
approximately 70% of etiological effects. Studies have found many significant genetic and …
approximately 70% of etiological effects. Studies have found many significant genetic and …
Polygenic risk scores in Alzheimer's disease: current applications and future directions
E Baker, V Escott-Price - Frontiers in Digital Health, 2020 - frontiersin.org
Genome-wide association studies have identified nearly 40 genome-wide significant single
nucleotide polymorphisms (SNPs) which are associated with Alzheimer's Disease (AD). Due …
nucleotide polymorphisms (SNPs) which are associated with Alzheimer's Disease (AD). Due …
In silico identification of new genetic variations as potential risk factors for Alzheimer's disease in a microarray-oriented simulation
RR Lemos, CH Castelletti, JL Lima Filho… - Journal of molecular …, 2009 - Springer
Genomic and proteomic studies of neurodegenerative disorders require complementary
approaches to integrate the massive amount of data generated in high throughput …
approaches to integrate the massive amount of data generated in high throughput …