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Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Bae et al. | Jan 22, 2024

Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.

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How are genetically modified foods discussed on TikTok? An analysis of #GMOFOODS

Basch et al. | Nov 20, 2023

How are genetically modified foods discussed on TikTok? An analysis of #GMOFOODS
Image credit: Camilo Jimenez

Here, the authors investigated engagement with #GMOFOODS, a hashtag on TikTok. They hypothesized that content focused on the negative effects of genetically modified organisms would receive more interaction driven by consumers. They found that the most common cateogry focused on the disadvantages of GMOs related to nutrition and health with the number of views determining if the video would be provided to users.

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Automated classification of nebulae using deep learning & machine learning for enhanced discovery

Nair et al. | Feb 01, 2024

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

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Bacteroides thetaiotaomicron Growth Numbers Are Unchanged in the Presence of Yogurt

Phan et al. | Dec 29, 2016

<i>Bacteroides thetaiotaomicron</i> Growth Numbers Are Unchanged in the Presence of Yogurt

Disruptions to the microbiome, specifically the imbalance in the two major phyla, the Firmicutes and the Bacteroidetes, have been linked to the development of obesity. This study explored whether or not Fage plain total 0% Greek yogurt, which contains live and active bacterial cultures belonging to the Firmicute phylum, could decrease the numbers of Bacteroides thetaiotaomicron, an organism found in the human gut that belongs to the Bacteroidetes phylum.

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Artificial Intelligence Networks Towards Learning Without Forgetting

Kreiman et al. | Oct 26, 2018

Artificial Intelligence Networks Towards Learning Without Forgetting

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

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Glyphosate Levels in American Food Products Meet Government Safety Levels Yet Exceed Concentrations Associated with Negative Effects

Lee et al. | Mar 25, 2019

Glyphosate Levels in American Food Products Meet Government Safety Levels Yet Exceed Concentrations Associated with Negative Effects

Glyphosate is the active ingredient in the herbicide Roundup, frequently used in the agricultural industry worldwide. Current literature reveals contradictory findings regarding the effects of glyphosate on vertebrates, leading to concerns about human consumption and differing views on safety levels. Here, authors sought to measure glyphosate levels in common commercially available food products. While some product levels exceed the thresholds at which negative effects have been observed, none exceed government limits.

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