AIMC Topic: Algorithms

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Reply: Deep Learning With Unsupervised Feature in Echocardiographic Imaging.

Journal of the American College of Cardiology Apr 25, 2017
Algorithms Echocardiography Deep Learning
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Deep Learning With Unsupervised Feature in Echocardiographic Imaging.

Journal of the American College of Cardiology Apr 25, 2017
Algorithms Echocardiography Deep Learning Machine Learning
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Sequence-based predictive modeling to identify cancerlectins.

Oncotarget Apr 25, 2017
Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a wide distribution to various species. They can specially identify and exclusively bind to a certain kind of saccharide groups. Cancerlectins are a group of lecti...
Amino Acid Sequence Lectins Humans Algorithms Reproducibility of Results Support Vector Machine Databases, Protein Neoplasms ROC Curve
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Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.

Oncotarget Apr 4, 2017
Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has...
Protein Interaction Mapping Saccharomyces cerevisiae Proteins Computational Biology Support Vector Machine Databases, Protein Bacterial Proteins Helicobacter pylori Saccharomyces cerevisiae Algorithms Reproducibility of Results Protein Binding Humans
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River flood prediction using fuzzy neural networks: an investigation on automated network architecture.

Water science and technology : a journal of the International Association on Water Pollution Research Apr 1, 2017
Urban floods are one of the most devastating natural disasters globally and improved flood prediction is essential for better flood management. Today, high-resolution real-time datasets for flood-related variables are widely available. These data can...
Models, Theoretical Fuzzy Logic Rivers Uncertainty Disasters Floods Neural Networks, Computer Algorithms Canada
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Unity is Strength: Improving biomedical classification performance based on ensemble learning approaches.

Computer methods and programs in biomedicine Apr 1, 2017
Algorithms Tomography, X-Ray Computed Diagnosis, Computer-Assisted Humans Electroencephalography Supervised Machine Learning Image Interpretation, Computer-Assisted Autistic Disorder Decision Support Systems, Clinical Lung Neoplasms Computational Biology
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Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

Transplantation Apr 1, 2017
BACKGROUND: The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritiz...
ROC Curve Tissue Donors Graft Survival Risk Assessment Adolescent Patient Selection Time Factors Reproducibility of Results Treatment Failure Risk Factors Male Donor Selection Aged Decision Support Techniques Middle Aged Predictive Value of Tests Victoria Databases, Factual Young Adult Humans Area Under Curve Female Machine Learning Liver Transplantation Adult Algorithms
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Protein subcellular localization prediction using multiple kernel learning based support vector machine.

Molecular bioSystems Mar 28, 2017
Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered...
Datasets as Topic Algorithms Protein Transport Reproducibility of Results Intracellular Space Computational Biology Support Vector Machine Proteins
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Prediction of acute toxicity of emerging contaminants on the water flea Daphnia magna by Ant Colony Optimization-Support Vector Machine QSTR models.

Environmental science. Processes & impacts Mar 22, 2017
According to the European REACH Directive, the acute toxicity towards Daphnia magna should be assessed for any industrial chemical with a market volume of more than 1 t/a. Therefore, it is highly recommended to determine the toxicity at a certain con...
Daphnia Quantitative Structure-Activity Relationship Toxicity Tests, Acute Models, Theoretical Support Vector Machine Algorithms Water Pollutants, Chemical Animals Surface-Active Agents Quaternary Ammonium Compounds
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[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Mar 20, 2017
OBJECTIVE: To establish a machine learning model based on gut microbiota for predicting the level of trimethylamine N-oxide (TMAO) metabolism in vivo after choline intake to provide guidance of individualized precision diet and evidence for screening...
Eggs Healthy Volunteers Choline Methylamines Gastrointestinal Microbiome Humans RNA, Ribosomal, 16S Machine Learning Oxides Algorithms
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