Objective: This study aimed to develop and validate an interpretable machine learning model specifically for multiclass hepatic steatosis severity prediction in nonobese individuals to support early ...

Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...

The human brain is known to naturally change with age, shrinking in size and volume after people reach their 30s or 40s. In ...

Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

Abstract: In this article, we propose using new machine learning (ML)-based optimization methods as an alternative to traditional optimization methods, for complex antenna designs. This is an ...

While machine learning (ML) has garnered increasing attention in health care applications, effective early prediction tools remain limited in current clinical practice. Recent investigations have ...

Department of Neurology, Weill Institute for Neuroscience, University of California San Francisco, San Francisco, California 94158, United States ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ('WiMi' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, announced that they are researching the use of neural ...

Chronic wounds remain a major health care challenge, especially for people with diabetes, who often experience delayed ...