Over the past few decades, electronics engineers have been trying to develop new neuromorphic hardware, systems that mirror the organization of neurons in the human brain. These systems could run ...

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

Background: Liver failure is associated with high short-term mortality, and the predictive value of clinical factors for patients undergoing artificial liver therapy is uncertain. We aim to develop ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Abstract: Cardiovascular diseases are a significant reason of suffering and several healthy years of lives lost as well as deaths in the world at large. There is the possibility of significantly ...