A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...
Abstract: Machine learning with small datasets presents well-known challenges, including overfitting and unreliable estimates. While fuzzy logic provides a framework for handling uncertainty, existing ...
Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and improve prognosis ...
ABSTRACT: We consider various tasks of recognizing properties of DRSs (Decision Rule Systems) in this paper. As solution algorithms, DDTs (Deterministic Decision Trees) and NDTs (Nondeterministic ...
ABSTRACT: Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...
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