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Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.
International journal of medical informatics
Sep 2, 2017
PURPOSE: This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing.
Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 1, 2017
Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the class...
Breast cancer cell nuclei classification in histopathology images using deep neural networks.
International journal of computer assisted radiology and surgery
Aug 31, 2017
PURPOSE: Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of c...
CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.
International journal of molecular sciences
Aug 31, 2017
Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results i...
The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.
Computer methods and programs in biomedicine
Aug 30, 2017
BACKGROUND AND OBJECTIVES: We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (explor...
Convolutional neural networks for automated annotation of cellular cryo-electron tomograms.
Nature methods
Aug 28, 2017
Cellular electron cryotomography offers researchers the ability to observe macromolecules frozen in action in situ, but a primary challenge with this technique is identifying molecular components within the crowded cellular environment. We introduce ...
Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study.
Forensic science, medicine, and pathology
Aug 18, 2017
Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be gene...
Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.
Artificial intelligence in medicine
Aug 14, 2017
OBJECTIVE: Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an on...
An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement.
NeuroImage
Aug 12, 2017
This paper presents an open, multi-vendor, multi-field strength magnetic resonance (MR) T1-weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The dataset is composed of images of older healthy adults (29-80 years) acquire...
Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.
Journal of healthcare engineering
Aug 9, 2017
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...
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