Objectives This study aims to explore the history of prior abortions and the factors influencing them among young women seeking abortion services in Foshan, Guangdong, China. Design This is a ...

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 ...

Abstract: With the widespread adoption of Noninvasive Prenatal Testing (NIPT), selecting an appropriate testing time has become critical for improving test accuracy. This study proposes a personalized ...

The term, long considered a slur for those with intellectual disabilities, is seeing a resurgence on social media and across the political right. By Dan Barry and Sonia A. Rao Late last month, a woman ...

Commonly used linear regression focuses only on the effect on the mean value of the dependent variable and may not be useful in situations where relationships across the distribution are of interest.

Abstract: Eco-driving has emerged as a promising approach to reducing fuel consumption in road vehicles by optimizing driving behavior for enhanced system efficiency. This paper formulates the ...

This project implements a Dynamic Programming (DP) solution for optimal inventory control, inspired by fundamental principles in Dimitri Bertsekas's work on "Lessons from AlphaZero for Optimal, Model ...

From IDE plugins to external chatbots and running LLMs locally, these new and emerging tools are bringing the generative AI revolution to R. My previous article focused on some of the best tools for ...