Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.
Heidi A HansonClaire L LeiserBrock O'NeilChristopher B DechetSumati GuptaKen R SmithWilliam T LowranceMichael J MadsenNicola J CampPublished in: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (2020)
FMC configurations could permit better definitions of cancer phenotypes (subtypes or multicancer) for gene discovery and environmental risk factor studies.
Keyphrases
- big data
- machine learning
- papillary thyroid
- risk factors
- artificial intelligence
- small molecule
- spinal cord injury
- squamous cell
- genome wide
- electronic health record
- copy number
- early onset
- lymph node metastasis
- human health
- case control
- childhood cancer
- risk assessment
- squamous cell carcinoma
- gene expression
- urinary tract
- young adults
- life cycle
- data analysis
- single cell