The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

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

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

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

While the potential benefits of AI in obesity prevention are substantial, the study devotes significant attention to ...

Eggs are more than just a breakfast staple – they’re a global nutritional powerhouse packed with essential vitamins, minerals ...

Background: Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and ...

Three people were reported in critical condition. Four people were injured when gunfire erupted in a crowd during an annual Christmas tree lighting ceremony in Concord, North Carolina, according to ...

“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

In the swiftly evolving tech landscape, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as two of the most ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...