AIMC Topic: Datasets as Topic

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Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification.

Computational intelligence and neuroscience
We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring ...

ReCAP: Feasibility and Accuracy of Extracting Cancer Stage Information From Narrative Electronic Health Record Data.

Journal of oncology practice
PURPOSE: Cancer stage, one of the most important prognostic factors for cancer-specific survival, is often documented in narrative form in electronic health records (EHRs). Such documentation results in tedious and time-consuming abstraction efforts ...

A decentralized training algorithm for Echo State Networks in distributed big data applications.

Neural networks : the official journal of the International Neural Network Society
The current big data deluge requires innovative solutions for performing efficient inference on large, heterogeneous amounts of information. Apart from the known challenges deriving from high volume and velocity, real-world big data applications may ...

Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Traditional Chinese medicine (TCM) is a unique and complex medical system that has developed over thousands of years. This article studies the problem of automatically extracting meaningful relations of entities from TCM literature, for th...

KnowEnG: a knowledge engine for genomics.

Journal of the American Medical Informatics Association : JAMIA
We describe here the vision, motivations, and research plans of the National Institutes of Health Center for Excellence in Big Data Computing at the University of Illinois, Urbana-Champaign. The Center is organized around the construction of "Knowled...

Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs.

Neural networks : the official journal of the International Neural Network Society
Support Vector Machines (SVMs) form a family of popular classifier algorithms originally developed to solve two-class classification problems. However, SVMs are likely to perform poorly in situations with data imbalance between the classes, particula...

The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...

Vascular segmentation in hepatic CT images using adaptive threshold fuzzy connectedness method.

Biomedical engineering online
BACKGROUND: Fuzzy connectedness method has shown its effectiveness for fuzzy object extraction in recent years. However, two problems may occur when applying it to hepatic vessel segmentation task. One is the excessive computational cost, and the oth...

Automated tracing of myelinated axons and detection of the nodes of Ranvier in serial images of peripheral nerves.

Journal of microscopy
The development of realistic neuroanatomical models of peripheral nerves for simulation purposes requires the reconstruction of the morphology of the myelinated fibres in the nerve, including their nodes of Ranvier. Currently, this information has to...

Domain adaptation for semantic role labeling of clinical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Semantic role labeling (SRL), which extracts a shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding natural language. Few studies in SRL have been conducted in...