Journal of chemical information and modeling
Jun 13, 2019
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in t...
BACKGROUND: CRISPR-Cpf1 has recently been reported as another RNA-guided endonuclease of class 2 CRISPR-Cas system, which expands the molecular biology toolkit for genome editing. However, most of the online tools and applications to date have been d...
Artificial intelligence (AI) has been present in some guise within the field of radiology for over 50 years. The first studies investigating computer-aided diagnosis in thoracic radiology date back to the 1960s, and in the subsequent years, the main ...
A novel method to detect and classify several classes of diseased and healthy lung tissue in CT (Computed Tomography), based on the fusion of Riesz and deep learning features, is presented. First, discriminative parametric lung tissue texture signatu...
Using a smart method for automatic diagnosis in medical applications, such as sleep stage classification is considered as one of the important challenges of the last few years which can replace the time-consuming process of visual inspection done by ...
BACKGROUND: Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.
The evaluation of large amounts of digital image data is of growing importance for biology, including for the exploration and monitoring of marine habitats. However, only a tiny percentage of the image data collected is evaluated by marine biologists...
Recent methodological innovations in deep learning and associated advancements in computational hardware have significantly impacted the various core subfields of quantitative medical image analysis. The generalizability, computational efficiency and...
PURPOSE: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).
With the rapid development of image scanning techniques and visualization software, whole slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis from pathology images and automating image analysis efficiently and...
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