بدائل البحث:
decision optimization » design optimization (توسيع البحث), bayesian optimization (توسيع البحث), driven optimization (توسيع البحث)
codon optimization » wolf optimization (توسيع البحث)
risk decision » xlink decision (توسيع البحث), time decision (توسيع البحث), ai decision (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
decision optimization » design optimization (توسيع البحث), bayesian optimization (توسيع البحث), driven optimization (توسيع البحث)
codon optimization » wolf optimization (توسيع البحث)
risk decision » xlink decision (توسيع البحث), time decision (توسيع البحث), ai decision (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
-
1
Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
منشور في 2021"…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …"
-
2
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…<br>The consistency of the results across different kernels demonstrates that the information contained in the habitat, by itself, leads to a very simple optimal decision rule (mostly the prediction of the most frequent class per habitat), which cannot be improved solely by model adjustments. …"
-
3
Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx
منشور في 2022"…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. We performed threshold optimization for converting predicted probabilities into binary predictions and identified the cut-off maximizing the sum of sensitivity and specificity.…"