The recognition of human activities is usually considered to be a simple procedure. Problems occur in complex scenes involving high speeds. Activity prediction using Artificial Intelligence (AI) by numerical analysis has attracted the attention of se...
Quantitatively determining in vivo achievable drug concentrations in targeted organs of animal models and subsequent target engagement confirmation is a challenge to drug discovery and translation due to lack of bioassay technologies that can discrim...
To better address the recognition of abnormalities among mammographic images, in this study we apply the deep fusion learning approach based on Pre-trained models to discover the discriminative patterns between Normal and Tumor categories. We designe...
Algorithms can improve the objectivity and efficiency of histopathologic slide analysis. In this paper, we investigated the impact of scanning systems (scanners) and cycle-GAN-based normalization on algorithm performance, by comparing different deep ...
Deep learning with Convolutional Neural Networks has shown great promise in image-based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation ap...
IMPORTANCE: Deep learning, a family of machine learning models that use artificial neural networks, has achieved great success at predicting outcomes in nonmedical domains.
Computational and mathematical methods in medicine
Sep 1, 2020
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method fo...
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Aug 31, 2020
BACKGROUND: Although great advances in artificial intelligence for interpreting small bowel capsule endoscopy (SBCE) images have been made in recent years, its practical use is still limited. The aim of this study was to develop a more practical conv...
BACKGROUND: The discovery of the CRISPR-Cas9-based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the...
Journal of voice : official journal of the Voice Foundation
Aug 30, 2020
OBJECTIVES: Deep learning using convolutional neural networks (CNNs) is widely used in medical imaging research. This study was performed to investigate if vocal fold normality in laryngoscopic images can be determined by CNN-based deep learning and ...
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