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Today's Water Cooler

The classification of medical images is significant among researchers and physicians for the early identification and clinical treatment of many disorders. Though, traditional classifiers require more time and effort for feature extraction and reduction from images. To overcome this problem, there is a need for a new deep learning method known as Convolution Neural Network (CNN), which shows the high performance and self-learning capabilities. In this paper,to classify whether a chest X-ray (CXR...

Lung cancer is the main cause of cancer death in the United States and around the world. Low-dose chest computed tomography (LDCT) is suggested for monitoring p

Press release CLINICAL DEMONSTRATION OF ZENEO® EFFICIENCY FOR INTRAMUSCULAR INJECTION OF MIDAZOLAM • Primary endpoints met and results in line with...

Here's an overview of various energy source trade-offs, and an outline of why energy prices are still likely to be an ongoing concern, globally.

Recently conducted research found that there is a significant correlation between serum Thyroid-stimulating hormone levels and Hepatitis B virus-related Acute-on-Chronic Liver Failure patients...

AQST-109 is the first and only orally delivered epinephrine product candidate in clinical developmentFastest median time to maximum concentration (Tmax) in...

/PRNewswire/ -- Lunit, a leading medical AI provider, today announced a supply agreement with the Korean National IT Industry Promotion Agency (NIPA) as part...

In a small but rigorous pilot study, Johns Hopkins Medicine researchers have shown that a novel, minimally invasive biomarker-based strategy they developed was 90% successful in detecting esophageal squamous cell carcinoma (ESCC), the predominant sub

In a small but rigorous pilot study, Johns Hopkins Medicine researchers have shown that a novel, minimally invasive biomarker-based strategy they developed was 90% successful in detecting esophageal squamous cell carcinoma (ESCC), the predominant subtype of esophageal cancer worldwide.