Neural networks : the official journal of the International Neural Network Society
Mar 14, 2020
Field classification is a new extension of traditional classification frameworks that attempts to utilize consistent information from a group of samples (termed fields). By forgoing the independent identically distributed (i.i.d.) assumption, field c...
We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our anal...
Personal Thermal Comfort models consider personal user feedback as a target value. The growing development of integrated "smart" devices following the concept of the Internet of Things and data-processing algorithms based on Machine Learning techniqu...
BACKGROUND: The selection and prioritization of drug targets is a central problem in drug discovery. Computational approaches can leverage the growing number of large-scale human genomics and proteomics data to make in-silico target identification, r...
Neural networks : the official journal of the International Neural Network Society
Mar 13, 2020
Non-negative matrix factorization (NMF) is a knowledge discovery method that is used in many fields. Variational inference and Gibbs sampling methods for it are also well-known. However, the variational approximation error has not been clarified yet,...
Neural networks : the official journal of the International Neural Network Society
Mar 13, 2020
Although it is one of the most widely used methods in recommender systems, Collaborative Filtering (CF) still has difficulties in modeling non-linear user-item interactions. Complementary to this, recently developed deep generative model variants (e....
Similarity-based search of sequence collections is a core task in bioinformatics, one dominated for most of the genomic era by exact and heuristic alignment-based algorithms. However, even efficient heuristics such as BLAST may not scale to the data ...
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
OBJECTIVE: To enhance the positive predictive value (PPV) of chest digital tomosynthesis (DTS) in the lung cancer detection with the analysis of radiomics features.
In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second p...
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