A perspective on genetic and polygenic risk scores—advances and limitations and overview of associated tools

J Schwarzerova, M Hurta, V Barton… - Briefings in …, 2024 - academic.oup.com
Abstract Polygenetic Risk Scores are used to evaluate an individual's vulnerability to
developing specific diseases or conditions based on their genetic composition, by taking …

Epistatic features and machine learning improve Alzheimer's disease risk prediction over polygenic risk scores

S Hermes, J Cady, S Armentrout… - Journal of …, 2024 - journals.sagepub.com
Background: Polygenic risk scores (PRS) are linear combinations of genetic markers
weighted by effect size that are commonly used to predict disease risk. For complex …

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes

NB Gunter, RK Gebre, J Graff-Radford… - Neurology …, 2024 - AAN Enterprises
Background and Objectives Alzheimer disease (AD) has a polygenic architecture, for which
genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) …

Developing SNP Interaction Polygenic Risk Scores (PRS-int Scores)

I Sarkar - 2024 - search.proquest.com
Understanding the intricate relationship between an individual's genetic variants
(genotypes) and their observable traits (phenotypes) is imperative for comprehending the …

[PDF][PDF] Integrating genetic markers and adiabatic quantum machine learning to improve disease resistance-based marker assisted plant selection

ETA Albert, NH Bille, BJ Martin… - Journal of Scientific …, 2023 - pdfs.semanticscholar.org
The goal of this research was to create a more accurate and efficient method for selecting
plants with disease resistance using a combination of genetic markers and advanced …

NetPRS: SNP interaction aware network-based polygenic risk score for Alzheimer's disease

S Park, D Lee, J Kim, D Kim, CH Hong, SJ Son… - … on Biomedical and … - openreview.net
Alzheimer's disease (AD) is underscored by its polygenic nature, attributable to variants
across multiple genetic loci. This has led to the development of the polygenic risk score …

Machine learning for precision medicine: a combination of data-driven and physics based models

NR Franco - 2022 - politesi.polimi.it
Precision medicine aims at improving the clinical treatment of patients by proposing subject-
specific therapies, which are designed on the basis of individual characteristics, such as age …