Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Urine-based aging clocks In the study, " A urinary microRNA aging clock accurately predicts biological age," published in npj Aging, researchers used machine learning to develop and validate a urinary ...

In a comprehensive new study, economists have redefined the boundaries of predictive modeling in economics, blending traditional macroeconomic analysis with advanced machine learning principles. The ...

(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

ABSTRACT: Dementia is a progressive neurodegenerative disorder that significantly impacts cognitive function, with early and accurate diagnosis remaining a clinical challenge. Traditional diagnostic ...

ABSTRACT: Dementia is a progressive neurodegenerative disorder that significantly impacts cognitive function, with early and accurate diagnosis remaining a clinical challenge. Traditional diagnostic ...

Abstract: Accurate path loss (PL) modeling in complex environments, such as underground mines, is essential for the deployment of the next-generation wireless networks. This article presents a deep ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...

Researchers have developed a machine learning-based approach to accurately predict the compressive strength of concrete made with industrial waste, offering a faster and more efficient alternative to ...