Predictive risk scores created using administrative claims and publicly available social determinants of health data strongly predicted severe diabetes complications for Maryland Medicare ...

Quadratic regression is a classical machine learning technique to predict a single numeric value. Quadratic regression is an extension of basic linear regression. Quadratic regression can deal with ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

The risk of ischemic stroke is highest during the first year following a new diagnosis of cancer, but no tools exist to identify patients at highest risk. Using linked clinical and administrative ...

Want to understand how multivariate linear regression really works under the hood? In this video, we build it from scratch in C++—no machine learning libraries, just raw code and linear algebra. Ideal ...

Abstract: Quantum neural networks (QNNs) have shown remarkable potential due to their capability of representing complex functions within exponentially large Hilbert spaces. However, their application ...

Abstract: The log-binomial regression model is an essential tool for performing relative risk regression to analyze binary outcomes. The Hotelling T2 Control Chart is an effective multivariate process ...

ABSTRACT: This article critically assessed the validity of five multiple linear regression models across three separate studies. The first examined the cytotoxic properties of ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

The NAPFA score integrates clinical features to streamline pediatric food allergy diagnosis, potentially reducing delays and costs. Food allergies affect 8% of children under 5, with diagnostic delays ...