AIMC Topic: Benchmarking

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Traditional Chinese medicine clinical records classification with BERT and domain specific corpora.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
Traditional Chinese Medicine (TCM) has been developed for several thousand years and plays a significant role in health care for Chinese people. This paper studies the problem of classifying TCM clinical records into 5 main disease categories in TCM....
Natural Language Processing Benchmarking Datasets as Topic Medical Records Deep Learning Medicine, Chinese Traditional
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ML-Net: multi-label classification of biomedical texts with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: In multi-label text classification, each textual document is assigned 1 or more labels. As an important task that has broad applications in biomedicine, a number of different computational methods have been proposed. Many of these methods,...
Computational Biology Natural Language Processing Benchmarking Data Mining Neural Networks, Computer Machine Learning Deep Learning Classification
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mCSM-PPI2: predicting the effects of mutations on protein-protein interactions.

Nucleic acids research Jul 2, 2019
Protein-protein Interactions are involved in most fundamental biological processes, with disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a novel machine learning computational tool designed to more accurately predic...
Protein Interaction Mapping Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Binding Sites Thermodynamics Mutation, Missense Software Protein Binding Proteins Datasets as Topic Crystallography, X-Ray Internet Benchmarking Humans Machine Learning
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PrankWeb: a web server for ligand binding site prediction and visualization.

Nucleic acids research Jul 2, 2019
PrankWeb is an online resource providing an interface to P2Rank, a state-of-the-art method for ligand binding site prediction. P2Rank is a template-free machine learning method based on the prediction of local chemical neighborhood ligandability cent...
Binding Sites Thermodynamics Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Amino Acid Sequence Ligands Datasets as Topic Protein Conformation, beta-Strand Humans Machine Learning Software Internet Benchmarking Protein Binding Proteins
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NetGO: improving large-scale protein function prediction with massive network information.

Nucleic acids research Jul 2, 2019
Automated function prediction (AFP) of proteins is of great significance in biology. AFP can be regarded as a problem of the large-scale multi-label classification where a protein can be associated with multiple gene ontology terms as its labels. Bas...
Software Animals Computational Biology Proteins Humans Machine Learning Molecular Sequence Annotation Databases, Protein Internet Gene Ontology Structure-Activity Relationship Benchmarking Models, Molecular Plants Protein Interaction Mapping Sequence Analysis, Protein Sequence Alignment Amino Acid Sequence Prokaryotic Cells Sequence Homology, Amino Acid
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Cross-type biomedical named entity recognition with deep multi-task learning.

Bioinformatics (Oxford, England) May 15, 2019
MOTIVATION: State-of-the-art biomedical named entity recognition (BioNER) systems often require handcrafted features specific to each entity type, such as genes, chemicals and diseases. Although recent studies explored using neural network models for...
Deep Learning Benchmarking Neural Networks, Computer Software
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Regulation of predictive analytics in medicine.

Science (New York, N.Y.) Feb 22, 2019
Humans Artificial Intelligence Algorithms Benchmarking United States Food and Drug Administration Decision Support Techniques United States Evidence-Based Medicine
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Identification of microRNA precursors using reduced and hybrid features.

Molecular bioSystems Jul 25, 2017
MicroRNAs (also called miRNAs) are a group of short non-coding RNA molecules. They play a vital role in the gene expression of transcriptional and post-transcriptional processes. However, abnormality of their expression has been observed in cancer, h...
Datasets as Topic RNA Precursors Multifactor Dimensionality Reduction MicroRNAs Humans Least-Squares Analysis Sequence Analysis, RNA Benchmarking Support Vector Machine
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iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines.

Molecular bioSystems Jul 25, 2017
Protein phosphorylation plays a potential role in regulating protein conformation and functions. As a result, identifying an uncharacterized protein sequence as a phosphorylated protein is a very meaningful problem and an urgent issue for both basic ...
Internet Benchmarking Datasets as Topic Tyrosine Protein Processing, Post-Translational Serine Computational Biology Humans Proteins Threonine Software Support Vector Machine Phosphorylation
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An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

Molecular bioSystems Jul 25, 2017
Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems...
Phenotype Codon Genotype Machine Learning Escherichia coli K12 Genes, Essential Benchmarking Base Composition Caulobacteraceae Metabolic Networks and Pathways Helicobacter pylori Datasets as Topic
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