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In light of this, a reliability and functional transition diagram used to model the RVS machine subsystems prognosis algorithms is depicted in Fig. 5.
The maintenance system model unfolds the predictive (i.e. diagnosis and prognosis) algorithms, the e-maintenance strategic tools as well as the dynamic maintenance strategic algorithms required to effectively maintain the RVS machine.
CBM enabling technologies include sensing and monitoring, information processing, fault diagnosis and failure prognosis algorithms that are capable of detecting accurately and in a timely manner incipient failures and predicting the remaining useful life of failing components.
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Comparisons with seven other existing prognosis based algorithms along with IPRE (G) and IPRE (C) were also performed to demonstrate that the IPRE algorithm was more effective and outperformed other existing algorithms.
Better classification: able to outperform the accuracy of seven other popular representative prognosis based algorithms.
Another key goal of prognosis prediction algorithms is to be applicable across data collected from different cohorts of patients.
A major challenge of prognosis prediction algorithms is to make them generically applicable to different human cancers.
The classification results on the 1,794 dataset, the 2,268 dataset, and the two testing datasets, in addition to a comparison with other popular existing prognosis based algorithms, are detailed in the following subsections.
We propose a novel algorithm called the IPRE (integrated prognosis risk estimation) algorithm.
We proposed a prognosis based classification algorithm to categorize breast cancer patients as high versus low risk.
To accomplish this aim, we propose a breast cancer prognosis based classification algorithm by developing a virtual chromosome (VC) consisting of two components (correlation-factor and penalized-factor), which are used to extract our prognostic gene signature that consists of 79 genes.
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