Sentence examples for models predicting disease from inspiring English sources

Multivariate binary logistical regression models predicting disease severity were constructed using patient characteristics, adjusted NPA cytokine concentrations and adjusted NPA hRSV load (table 3).

Understanding variation in pathogen virulence is essential to create accurate epidemiological models, predict disease outcomes, and understand mechanisms of pathogenicity (Jones et al. 2008).

Note: : model predicted disease status (1 for yes, 0 for no); y: diagnosed disease status (1 for yes, 0 for no).

We are exploring analytic models of predicting disease risk using established and innovative statistical methodology.

Spatial clustering techniques are essential for statistical consideration and form the starting approach in the development of models for predicting disease risk sites.

In the current study, we describe results of an independent evaluation of models for predicting disease stage and response to platin-based chemotherapy built on the data of the pilot.

The results of our study emphasize the importance of considering virulence on an isolate-specific basis when creating epidemiological models and predicting disease outcomes for this ecologically important pathogen.

The aim of the present multicentre study was to externally validate the EORTC risk tables and the CUETO scoring model for predicting disease recurrence and progression in NMIBC patients with or without BCG therapy.

These complexities notwithstanding, consensus within the scientific community on favorable approaches for modeling and predicting disease course is necessary to help regulatory and payor agencies make informed decisions about the approvability and accessibility of the next generation of pharmacological interventions.

A precise and detailed catalogue of events leading to full infection would better inform models aimed at predicting disease outcome and better inform the timing of fungicide spraying.

Of these, 296 values were from prognostic models (predicting a disease event in patients who already have the disease of interest) and 184 from risk models (predicting onset of a disease in healthy patients).