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Neoplasms, Radiation-Induced

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Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

PloS one 32106268
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two w...
Adult Breast Neoplasms Cancer Survivors Case-Control Studies Cohort Studies Female Genome-Wide Association Study Genotype Germ Cells Humans Machine Learning Neoplasms, Radiation-Induced Polymorphism, Single Nucleotide Risk Factors Young Adult
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A competing risks machine learning study of neutron dose, fractionation, age, and sex effects on mortality in 21,000 mice.

Scientific reports 39095647
This study explores the impact of densely-ionizing radiation on non-cancer and cancer diseases, focusing on dose, fractionation, age, and sex effects. Using historical mortality data from approximately 21,000 mice exposed to fission neutrons, we empl...
Age Factors Animals Dose Fractionation, Radiation Dose-Response Relationship, Radiation Female Machine Learning Male Mice Neoplasms, Radiation-Induced Neutrons Sex Factors
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Utilizing patient data: A tutorial on predicting second cancer with machine learning models.

Cancer medicine 39300964
BACKGROUND: The article explores the potential risk of secondary cancer (SC) due to radiation therapy (RT) and highlights the necessity for new modeling techniques to mitigate this risk.
Decision Trees Humans Machine Learning Neoplasms, Radiation-Induced Neoplasms, Second Primary Precision Medicine Risk Assessment Risk Factors
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