Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...
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 ...
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 ...
A new analysis of gene expression in blood samples suggests that specific biological signs of Parkinson’s disease are ...
Background Motor and cognitive dysfunctions are common and disabling features in multiple sclerosis (MS) that remain challenging to treat. Here, we aimed to explore the effect of exergames as a ...
Introduction Mobile health (mHealth) technologies have become increasingly popular for monitoring mental health symptoms and lifestyle behaviours, and are largely reported to be feasible and ...
Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...
LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...
By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.
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