A new tool makes it possible to screen millions of tiny protein fragments and select those that can be recognized by the ...

Bacterial immune systems protect against viral invaders called phages by precisely targeting specific phage genetic sequences ...

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

Retail LLMs promise raw computing power in edge settings. But what are the considerations that face decision-makers in the ...

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...

Acute sleep deprivation significantly impacts cognitive function, contributes to accidents, and increases the risk of chronic illnesses, underscoring the need for reliable and objective diagnosis. Our ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: With the advancement of deep learning techniques, deep neural networks have progressively supplanted traditional machine learning methods for hyperspectral image (HSI) classification, ...

Bipolar disorder is a complex psychiatric condition characterized by alternating mood episodes, ranging from depression to mania. Accurate and timely detection of a patient’s current mood state is ...

Abstract: In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to ...