Objectives To assess the outcomes of patients undergoing open abdominal surgery at a National Referral Hospital in Tanzania. Design A prospective, observational, single-arm cohort study. Setting Dar ...
Objective SLE is a heterogeneous systemic autoimmune disease with diverse clinical manifestations. We aimed to identify ...
Abstract: This paper presents techniques for segmentation and change classification using logistic regression. The research was conducted on SPOT 5 multispectral multitemporal images covering the 2010 ...
Abstract: Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical ...
ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...
1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
In the subject of machine learning, it is essential to comprehend regression algorithms. Ten fundamental regression algorithms are introduced in this tutorial, which serves as the foundation for many ...
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