Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

The Data Science Certification Program by Learnbay provides United States training which prepares early to mid-career professionals for job-ready skills. The pr ...

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

Finely dispersed particulate matter with a diameter of ≤2.5 μm (PM2.5) poses a significant health- and climate-risk, yet ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...

In a study published in npj Digital Medicine, a team of researchers led by the University of Michigan developed a machine learning model that identified 17 environmental and social factors that can ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...

New research shows mutual funds using machine learning strategies generate significant outperformance over traditional funds ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...