Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...

A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how systems evolve over time and reduces thousands of variables into compact ...

Introduction: Early diagnosis of Alzheimer's disease (AD) remains challenging due to the high similarity among AD, mild cognitive impairment (MCI), and cognitively normal (CN) individuals, as well as ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

Purpose: To develop and evaluate deep learning (DL) models for detecting multiple retinal diseases using bimodal imaging of color fundus photography (CFP) and optical coherence tomography (OCT), ...

Tensors are the fundamental building blocks in deep learning and neural networks. But what exactly are tensors, and why are they so important? In this video, we break down the concept of tensors in ...

Due to the limitations of collection conditions and costs, public brain network datasets generally combine data from multiple sites. However, the difference among multi-source data collected from ...

Russia’s intelligence services turned Brazil into an assembly line for deep-cover operatives. A team of federal agents from the South American country has been quietly dismantling it. By Michael ...

Spin glasses might turn out to be the most useful useless things ever discovered. These materials — which are typically made of metal, not glass — exhibit puzzling behaviors that captivated a small ...

Section 1. Background. The United States has a core national security and economic interest in maintaining leadership in deep sea science and technology and seabed mineral resources. The United States ...