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 ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

ABSTRACT: End-stage renal disease is one of the leading causes of mortality among the population in China. Maintenance hemodialysis (MHD), as an optimal treatment for end-stage renal disease, has ...

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 ...

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient ...

I’ll be honest: I never thought I’d like e-readers. I’ve been a bookworm ever since I was a young child, and I grew up surrounded by books. When e-readers came around, I could immediately see they ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...