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- W641517745 abstract "Dynamic Bayesian networks (DBNs) offer a framework for explicit modeling of temporal relationships. They are often used as prognostic tools. In medicine, for example, they can assist planning treatment options or clinical management of patients. They have been also widely applied to genomics and proteomics. This paper describes the Pittsburgh Cervical Cancer Screening Model (PCCSM), a DBN that combines two sources of knowledge: expert opinion and objective hospital data. The model serves as a convenient tool for assessing the risk of cervical precancer and invasive cervical cancer over time. These quantitative risk assessments are helpful for establishing the optimal timing of follow-up screening and are the first step toward generating individualized reevaluation scheduling." @default.
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- W641517745 date "2009-01-01" @default.
- W641517745 modified "2023-10-03" @default.
- W641517745 title "Application of Dynamic Bayesian Networks to cervical cancer screening" @default.
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