Sentence examples for generating a recommendation from inspiring English sources

For example, the CDSC rule queries lab data for evidence of microalbuminuria to justify generating a recommendation to start an ACE Inhibitor medication.

This pop-up screen will help remind the GP about the IMPaCT Back study and prompts completion of the subgrouping tool, automatically generating a recommendation about targeted treatment to support clinical decision making.

Beyond the technical and scientific expertise required to interpret cancer-related data and the challenges of cancer treatment trials, understanding the context of the disease, how patients present, expected outcomes, and challenges with currently available treatments are all critical to generating a recommendation relevant to patients, clinicians, and policy-makers.

The key difference is that Alfred is focused on keeping the number of taps required to generate a recommendation to a minimum — based on the time of day, the restaurants you've eaten at previously, and other factors, the app can generate a recommendation for lunch or coffee in a tap or two (find our past coverage here and here).

We're working on an application profiler where CIOs can enter information and generate a recommendation for how much memory-sharing they need and which chip is best for any given application.

Based on the prediction node sequence, we fill the user-item matrix step by step to generate a recommendation list, which can reduce the impact of a node's predication deviation on its nearest neighbors to really improve the prediction accuracy.

The expert advisory group aimed to generate a recommendation on the population impact of total fat intake in the development of obesity.

CARAT will then quantify the patient's estimated risk of stroke versus bleeding, flag pertinent medication management issues, and generate a recommendation for therapy (warfarin, aspirin, none, other).

First, the information system domain refers to the information system and the various processes undertaken by the firm(s) to generate a recommendation on the basis of the consumer's personal information.

This will involve performing an individualized risk assessment and generating a treatment recommendation for their patient by carefully assessing relevant risk factors for stroke, bleeding, medication misadventure and entering this data, as guided by CARAT, into the web-based platform.

The EFAES inference engine employs both case-based reasoning (CBR) and rule-based reasoning (RBR) to generate a hybrid recommendation list for cross validation.