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Though its specific applicability may vary slightly from industry to industry, our process provides a highly actionable model for deploying data analytics in a proactive, transformational manner; one that guides your decision making instead of justifying it.
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We present four change-based actionable models according to action benefit and action cost.
My goal is translate an improved molecular genetic and developmental understanding of congenital heart disease from the laboratory into clinically actionable models, diagnostics, and ultimately therapeutic interventions.
The framework, consists of six actionable models that include tools, processes infrastructures, and reflects the intersection of several theories and implementation science.
RE has gained strength and legitimacy from (1) harnessing then deconstructing, empirically and theoretically, the notion of 'human error', (2) argued for a system (and complexity) view and discourse about safety/accidents, (3) and supported this view with the help of (graphical) actionable models and methods (i.e. the engineering orientation).
"How do we, as machine-learning practitioners, handle societal problems while trying to make accurate, actionable models?" asks John Fahrenbach, a UCM data scientist who worked on the algorithm.
For these programs, we need to develop an appropriate IT framework, learn to train healthcare and wellness coaches, create effective and integrated data generation platforms and pioneer the analytical tools that will allow the creation of predictive and actionable models for each participant's data cloud.
Given these complex and variable hard-wired circuit disturbances, it is worth considering how new and emerging findings can be integrated into actionable treatment models.
As funding for all sectors of the arts is being squeezed, dance company directors are forced to apply their artistic creativity to actionable business models.
Although such network models have been developed in the past [ 11, 77], they have not been made actionable for the modeling of drug effects and pharmaceutical research and development.
Before adoption for clinical use, predictive models require considerable testing and re-adjustment, including internal validation, external validation with other populations, followed by determination if the validated model provides actionable information to the clinician and patient (Moons et al. 2012).
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