Reaching the end-game for GWAS: machine learning approaches for the prioritization of complex disease loci
Genome-wide association studies (GWAS) have revealed thousands of genetic loci that
underpin the complex biology of many human traits. However, the strength of GWAS–the …
underpin the complex biology of many human traits. However, the strength of GWAS–the …
Artificial intelligence in radiotherapy
G Li, X Wu, X Ma - Seminars in Cancer Biology, 2022 - Elsevier
Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
Machine learning-based models for prediction of toxicity outcomes in radiotherapy
In order to limit radiotherapy (RT)-related side effects, effective toxicity prediction and
assessment schemes are essential. In recent years, the growing interest toward artificial …
assessment schemes are essential. In recent years, the growing interest toward artificial …
Machine learning on a genome-wide association study to predict late genitourinary toxicity after prostate radiation therapy
S Lee, S Kerns, H Ostrer, B Rosenstein… - International Journal of …, 2018 - Elsevier
Purpose Late genitourinary (GU) toxicity after radiation therapy limits the quality of life of
prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose …
prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose …
[HTML][HTML] Machine learning approaches to genome-wide association studies
Abstract Genome-wide Association Studies (GWAS) are conducted to identify single
nucleotide polymorphisms (variants) associated with a phenotype within a specific …
nucleotide polymorphisms (variants) associated with a phenotype within a specific …
Genetic approaches to exploit landraces for improvement of Triticum turgidum ssp. durum in the age of climate change
C Broccanello, D Bellin, G DalCorso, A Furini… - Frontiers in Plant …, 2023 - frontiersin.org
Addressing the challenges of climate change and durum wheat production is becoming an
important driver for food and nutrition security in the Mediterranean area, where are located …
important driver for food and nutrition security in the Mediterranean area, where are located …
Genome-wide association study as a powerful tool for dissecting competitive traits in legumes
Legumes are extremely valuable because of their high protein content and several other
nutritional components. The major challenge lies in maintaining the quantity and quality of …
nutritional components. The major challenge lies in maintaining the quantity and quality of …
Machine learning and radiogenomics: lessons learned and future directions
Due to the rapid increase in the availability of patient data, there is significant interest in
precision medicine that could facilitate the development of a personalized treatment plan for …
precision medicine that could facilitate the development of a personalized treatment plan for …
Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs)
that optimally predict radiation-associated contralateral breast cancer (RCBC) and to …
that optimally predict radiation-associated contralateral breast cancer (RCBC) and to …
A deep learning approach validates genetic risk factors for late toxicity after prostate cancer radiotherapy in a REQUITE multi-national cohort
Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy
toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an …
toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an …