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Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jun 12, 2020
Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus cu...
R-ELMNet: Regularized extreme learning machine network.
Neural networks : the official journal of the International Neural Network Society
Jun 11, 2020
Principal component analysis network (PCANet), as an unsupervised shallow network, demonstrates noticeable effectiveness on datasets of various volumes. It carries a two-layer convolution with PCA as filter learning method, followed by a block-wise h...
A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.
Methods (San Diego, Calif.)
Jun 10, 2020
MOTIVATION: Alternative splicing makes significant contributions to functional diversity of transcripts and proteins. Many alternatively spliced gene isoforms have been shown to perform specific biological functions under different contexts. In addit...
Assessment of liver metastases radiomic feature reproducibility with deep-learning-based semi-automatic segmentation software.
Acta radiologica (Stockholm, Sweden : 1987)
Jun 9, 2020
BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable.
FastSurfer - A fast and accurate deep learning based neuroimaging pipeline.
NeuroImage
Jun 8, 2020
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands or tens of thousands of individuals. In this work we propose a fast and...
Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).
Molecular pharmaceutics
Jun 8, 2020
Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to xenobiotics in humans and the leading cause of postmarketing withdrawals of approved drugs. To date, these drugs have been collated by the FDA to form the DILIRank da...
CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.
Computer methods and programs in biomedicine
Jun 5, 2020
BACKGROUND AND OBJECTIVE: The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. It has so far infected around 1.8 million people and claimed approximately 114,698 lives overall. As...
Assistant diagnosis with Chinese electronic medical records based on CNN and BiLSTM with phrase-level and word-level attentions.
BMC bioinformatics
Jun 5, 2020
BACKGROUND: Inferring diseases related to the patient's electronic medical records (EMRs) is of great significance for assisting doctor diagnosis. Several recent prediction methods have shown that deep learning-based methods can learn the deep and co...
Using Reactome to build an autophagy mechanism knowledgebase.
Autophagy
Jun 2, 2020
The 21st century has revealed much about the fundamental cellular process of autophagy. Autophagy controls the catabolism and recycling of various cellular components both as a constitutive process and as a response to stress and foreign material inv...
Magnetic Elements for Neuromorphic Computing.
Molecules (Basel, Switzerland)
May 30, 2020
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann b...
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