A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Objectives Since 1985, the international healthcare community has recommended the ideal rate of caesarean section (CS) to be 10%–15% at the national level. The literature has reported that overused CS ...
Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...
a fast and accurate implementation of temperature scaling. an implementation of structured matrix scaling (SMS), a regularized version of matrix scaling that outperforms other logistic-based ...
Please provide your email address to receive an email when new articles are posted on . The WISEcode classification system graded ultra-processed foods more evenly vs. the NOVA system. The tool ...
Although mnemonic devices far predate the written word, both Cicero and Quintilian name Simonides of Ceos (c. 556-468 BCE) as the first teacher of an art of memory. Simonides is perhaps best known for ...
As biomarker studies employ increasingly complex and expensive genomics and other correlative methods, it is increasingly important to rigorously design these studies and analyze the downstream ...
aDepartment of Information and Computer Sciences, University of Hawaiʻi at Mānoa, POST Bldg, 1860 East-West Rd, Honolulu, HI, 96822, USA bUniversity of Hawaiʻi Cancer Center, 701 Ilalo St, Honolulu, ...
Abstract: Logistic regression is a supervised learning algorithm widely used in binary classification scenarios. It can predict the probability of time occurrence with probability. In this paper, to ...
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