Machine learning for detecting epistasis interactions and its relevance to personalized medicine in alzheimer's disease: Systematic review

MM Abd El Hamid, M Shaheen… - Biomedical …, 2021 - World Scientific
Alzheimer's disease (AD) is a progressive disease that attacks the brain's neurons and
causes problems in memory, thinking, and reasoning skills. Personalized Medicine (PM) …

Discovering Alzheimer genetic biomarkers using Bayesian networks

FF Sherif, N Zayed, M Fakhr - Advances in bioinformatics, 2015 - Wiley Online Library
Single nucleotide polymorphisms (SNPs) contribute most of the genetic variation to the
human genome. SNPs associate with many complex and common diseases like Alzheimer's …

Discovering epistasis interactions in Alzheimer's disease using deep learning model

MM Abd El Hamid, YMK Omar, M Shaheen… - Gene Reports, 2022 - Elsevier
Alzheimer's disease (AD) is the most common form of dementia. Single Nucleotide
Polymorphisms (SNPs) are single nucleotide alterations that can be used as genomic …

Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles

H Ahmed, L Alarabi, S El-Sappagh, H Soliman… - PeerJ Computer …, 2021 - peerj.com
Methods We used a methodology for literature surveys to obtain data from academic
databases. Criteria were defined for inclusion and exclusion. The selection of articles was …

Screening properties of trend tests in genetic association studies

Z Jiang, H Guo, J Wang - Scientific Reports, 2023 - nature.com
In genome-wide association study, extracting disease-associated genetic variants among
millions of single nucleotide polymorphisms is of great importance. When the response is a …

Using AI to Predict Radiotherapy Toxicity Risk Based on Patient Germline Genotyping

JH Oh, S Lee, M Thor, JO Deasy - Artificial Intelligence In Radiation …, 2023 - World Scientific
The collateral irradiation of normal tissues can result in damage that reduces the quality of
life for cancer survivors. The variability of toxicity risk has been increasingly recognized as …

Systems and methods for predicting treatment-regimen-related outcomes

E Rubenstein, ST Sonis, C De Moor - US Patent 10,475,539, 2019 - Google Patents
Abstract Systems and methods are provided for predicting treatment-regimen-related
outcomes (eg, risks of regimen-related toxicities). A predictive model is determined for …

[PDF][PDF] Support vector machines applied to the genetic classification problem of hybrid populations with high degrees of similarity

VP Carvalho, IC Sant'Anna, M Nascimento… - 2018 - funpecrp.com.br
Selection of appropriate genitors in breeding programs increases gains due to the variability
found in the divergent groups; this allows quantification of the existing variability, saving time …

Development of network-based analysis methods with application to the genetic component of asthma

Y Liu - 2017 - theses.hal.science
Genome-wide association studies (GWAS) of asthma have been successful in identifying
novel asthma-associated loci, but the genes at these loci account only for a part of the whole …

Methods for Information Content Analysis of Multimodal High-Throughput Biomedical Data

B Ray - 2017 - search.proquest.com
The spectrum of modern molecular high-throughput assays includes diverse technologies
such as microarrays, next generation sequencing, mass spectrometry and microscopy that …