Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

The PLA is already testing technologies that range from widespread sensors to AI-enabled predictive planning, cargo drones, ...

The report e-Commerce in the Mattress Industry was also carried out through direct interviews with leading mattress manufacturers and retailers operating in the e-commerce mattress business and an ...

Background The likelihood of HIV acquisition is increased following forced vaginal sex. This relates in part to ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Introduction Pre-exposure prophylaxis (PrEP) is an effective HIV prevention strategy, but its impact is limited by low uptake ...

Objectives To explore the levels of health-related functioning during pregnancy and postpartum and its association with non-severe maternal morbidities. Design An observational longitudinal study.

This article is a continuation of the 1st Stryker Brigade Combat Team (SBCT), 4th Infantry Division’s “Moneyball for Gunnery” ...

Abstract: Spiking neuron models are inspired by biological neurons. They can simulate the neuronal activities of the mammalian brains, such as spiking (integrator) and periodic oscillation (resonator) ...

Abstract: We present a new model for multivariate time-series classification, called the hidden-unit logistic model (HULM), that uses binary stochastic hidden units to model latent structure in the ...