Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Abstract: Pneumonia, a severe respiratory infection, remains a leading global cause of death, particularly among vulnerable populations such as children and the elderly, underscoring the importance of ...

Abstract: Text messaging (SMS) remains widely used due to its simplicity and accessibility. However, its popularity has led to a rise in spam messages, including ads, scams, and phishing links.

A complete implementation of Logistic Regression with Gradient Descent optimization from scratch using only NumPy, demonstrating mathematical foundations of binary classification for diabetes ...

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 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

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This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

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 ...