Machine learning SNP based prediction for precision medicine

DSW Ho, W Schierding, M Wake, R Saffery… - Frontiers in …, 2019 - frontiersin.org
In the past decade, precision genomics based medicine has emerged to provide tailored
and effective healthcare for patients depending upon their genetic features. Genome Wide …

Nutrition during childhood cancer treatment: current understanding and a path for future research

L Joffe, EJ Ladas - The Lancet Child & Adolescent Health, 2020 - thelancet.com
Proper nutritional status during cancer therapy has been recognised as being integral to a
variety of health outcome measures, including overall survival, treatment tolerance, and …

[HTML][HTML] Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome

AK Short, R Weber, N Kamei, CW Thai, H Arora… - Neurobiology of …, 2024 - Elsevier
Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the
enduring impact of ELA on cognitive and emotional health is established, there are no tools …

Predicting obesity and smoking using medication data: A machine‐learning approach

S Ali, R Na, M Waterhouse, SJ Jordan… - … and drug safety, 2022 - Wiley Online Library
Purpose Administrative health datasets are widely used in public health research but often
lack information about common confounders. We aimed to develop and validate machine …

Interaction of genetic and environmental factors for body fat mass control: observational study for lifestyle modification and genoty**

JH Kang, H Kim, J Kim, JH Seo, S Cha, H Oh, K Kim… - Scientific reports, 2021 - nature.com
Previous studies suggested that genetic, environmental factors and their interactions could
affect body fat mass (BFM). However, studies describing these effects were performed at a …

Artificial intelligence-enabled obesity prediction: A systematic review of cohort data analysis

SRN Kalhori, F Najafi, H Hasannejadasl… - International Journal of …, 2025 - Elsevier
Background Obesity, now the fifth leading global cause of death, has seen a dramatic rise in
prevalence over the last forty years. It significantly increases the risk of diseases such as …

Comprehensive and systematic analysis of gene expression patterns associated with body mass index

PV Joseph, RB Jaime-Lara, Y Wang, L **ang… - Scientific Reports, 2019 - nature.com
Both genetic and environmental factors are suggested to influence overweight and obesity
risks. Although individual loci and genes have been frequently shown to be associated with …

Deep Learning captures the effect of epistasis in multifactorial diseases

V Perelygin, A Kamelin, N Syzrantsev… - Frontiers in …, 2025 - frontiersin.org
Background Polygenic risk score (PRS) prediction is widely used to assess the risk of
diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are …

Data integration between clinical research and patient care: A framework for context-depending data sharing and in silico predictions

K Hoffmann, A Pelz, E Karg, A Gottschalk… - PLOS Digital …, 2023 - journals.plos.org
The transfer of new insights from basic or clinical research into clinical routine is usually a
lengthy and time-consuming process. Conversely, there are still many barriers to directly …

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome

AK Short, R Weber, N Kamei, CW Thai, H Arora… - …, 2023 - pmc.ncbi.nlm.nih.gov
Background. Adverse early-life experiences (ELA), including poverty, trauma and neglect,
affect a majority of the world's children. Whereas the impact of ELA on cognitive and …