Sentence examples for both classes of patient from inspiring English sources

Exact(1)

If no assumptions at all are made about the form of the CPDFs, these functions must be estimated from the training set (correctly classified cases for both classes of patient) by certain nonparametric methods [ 18].

Similar(59)

Although both classes of patients are deficient in UV-induced TC-NER, we have previously shown that CS cells are deficient in repair of oxidative DNA lesions [ 6].

CD34+ cells from both classes of CR AML patients showed AM network features that make these cells prone to apoptosis: accordingly, it is not surprising that these patients were in apparent CR after the first cycle of chemotherapy induction and consolidation.

Ng-Mak and colleagues recently found that in addition to the 11% of migraineurs who treated their most recent attack exclusively with an NSAID, triptan/NSAID co-therapy and using an NSAID as rescue medication were common practices when both classes of medication were available to patients [14].

This should allow for generation of new classes of patient specific PN/SN directed therapeutics for personalized management of the CFFL in the clinic.

The second grouping is context relevant and contains the classes of Patient Characteristics, Incident Characteristics, and Contributing Factors.

Cancer genomics is important for gliomas in the sense that it may help to define classes of patient with distinct prognoses and/or responses to therapeutic strategies.

The present study uniquely allows us to examine disease heterogeneity using biological and radiological data both individually, as well as collectively, to define homogeneous classes of patients or subtypes.

The model identified three main classes of patients: (1) low-risk WDNECs=patients with both LFTs and 5HIAA not significantly altered; (2) intermediate-risk WDNECs=patients with one of the two variables significantly altered; and (3) high-risk WDNECs=patients with both LFTs and 5HIAA significantly altered.

In this paper, hospital appointment systems with multiple classes of patients are considered where different classes of patients may vary in punctuality, no-show probabilities, mean service times and service time variability.

The performance measures of interest include the waiting times of all classes of patients and utilization of the server (MRI machine).

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