Exact(1)
Recommender technologies have been developed to give helpful predictions for decision making under uncertainty.
Similar(7)
Our approach permits more accurate land consumption prediction for decision-making in sustainable land utilization.
In addition, we have assessed the added value of such predictions for medical decision making.
Adding external data makes the prediction better for decision trees, but only up to a certain cost-per-instance of external data (between $5 and $10 in this case).
To validate our approach, we show how employing our language can improve the accuracy of predictions used for decision-making in the Rainbow framework for architecture-based self-adaptation.
The results show that the predictions of evapotranspiration, runoff and baseflow are hardly affected by the classification uncertainty when area-averaged predictions are intended, implying that uncertainty propagation is only advisable in case a spatial distribution of the predictions is relevant for decision making or is coupled to other spatially distributed models.
Beyond purely chronometric measures, this hypothesis establishes a critical prediction for simple decision tasks; If the processing stages involved in a cognitive task are merely rescheduled during dual task performance, the quality of the decision should be unaffected by a concurrent task.
Similarity search based on patient mutation profiles can solve various translational bioinformatics tasks, including prognostics and treatment efficacy predictions for better clinical decision making through large volume of data.
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