AIMC Topic:
Databases, Factual
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Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 30, 2016
Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminat...
Big Data and machine learning in radiation oncology: State of the art and future prospects.
Cancer letters
May 27, 2016
Precision medicine relies on an increasing amount of heterogeneous data. Advances in radiation oncology, through the use of CT Scan, dosimetry and imaging performed before each fraction, have generated a considerable flow of data that needs to be int...
Machine Learning
Decision Support Techniques
Databases, Factual
Humans
Neural Networks, Computer
Risk Assessment
Neoplasms
Support Vector Machine
Electronic Health Records
Risk Factors
Biomedical Research
Data Mining
Unsupervised Machine Learning
Radiotherapy Planning, Computer-Assisted
Radiotherapy
Data Interpretation, Statistical
Radiation Dosage
Radiation Oncology
Tracing Road Network Bottleneck by Data Driven Approach.
PloS one
May 26, 2016
Urban road congestions change both temporally and spatially. They are essentially caused by network bottlenecks. Therefore, understanding bottleneck dynamics is critical in the goal of reasonably allocating transportation resources. In general, a typ...
SWIFT-Review: a text-mining workbench for systematic review.
Systematic reviews
May 23, 2016
BACKGROUND: There is growing interest in using machine learning approaches to priority rank studies and reduce human burden in screening literature when conducting systematic reviews. In addition, identifying addressable questions during the problem ...
Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.
PloS one
May 19, 2016
This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious ...
BelSmile: a biomedical semantic role labeling approach for extracting biological expression language from text.
Database : the journal of biological databases and curation
May 12, 2016
Biological expression language (BEL) is one of the most popular languages to represent the causal and correlative relationships among biological events. Automatically extracting and representing biomedical events using BEL can help biologists quickly...
Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.
Journal of biomedical semantics
May 11, 2016
BACKGROUND: Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have be...
Clustering Single-Cell Expression Data Using Random Forest Graphs.
IEEE journal of biomedical and health informatics
May 10, 2016
Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as sing...
The Ontology for Biomedical Investigations.
PloS one
Apr 29, 2016
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide...
Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping.
Biomedical engineering online
Apr 26, 2016
BACKGROUND: Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sources or targeting complex fractionated electrograms in atrial fibrillation (AF). However, the incomple...
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