AIMC Topic: Electronic Data Processing

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Private naive bayes classification of personal biomedical data: Application in cancer data analysis.

Computers in biology and medicine Dec 24, 2018
Clinicians would benefit from access to predictive models for diagnosis, such as classification of tumors as malignant or benign, without compromising patients' privacy. In addition, the medical institutions and companies who own these medical inform...
Humans Bayes Theorem Models, Biological Electronic Data Processing Machine Learning Female Breast Neoplasms
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A Reweighted Scheme to Improve the Representation of the Neural Autoregressive Distribution Estimator.

Computational intelligence and neuroscience Dec 23, 2018
The neural autoregressive distribution estimator(NADE) is a competitive model for the task of density estimation in the field of machine learning. While NADE mainly focuses on the problem of estimating density, the ability for dealing with other task...
Machine Learning Electronic Data Processing Humans Data Analysis Neural Networks, Computer Algorithms
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PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

PloS one Dec 20, 2018
Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and...
Neural Networks, Computer Software Algorithms Humans Environmental Monitoring Malaysia Oryza Animals Deep Learning Agriculture Insect Control Insecta Pattern Recognition, Automated Electronic Data Processing
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The Role of a Deep-Learning Method for Negation Detection in Patient Cohort Identification from Electroencephalography Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Detecting negation in biomedical texts entails the automatic identification of negation cues (e.g. "never", "not", "no longer") as well as the scope of these cues. When medical concepts or terms are identified within the scope of a negation cue, thei...
Information Storage and Retrieval Humans Cohort Studies Deep Learning Electronic Data Processing Natural Language Processing Electroencephalography
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Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks.

PLoS computational biology Nov 20, 2018
Multiplexing, the simultaneous sequencing of multiple barcoded DNA samples on a single flow cell, has made Oxford Nanopore sequencing cost-effective for small genomes. However, it depends on the ability to sort the resulting sequencing reads by barco...
Software Algorithms Reproducibility of Results Neural Networks, Computer Nanotechnology High-Throughput Nucleotide Sequencing DNA Barcoding, Taxonomic Bacteria Computational Biology DNA Nanopores Electronic Data Processing Gene Library Genome
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A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Nature genetics Nov 5, 2018
Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consumin...
DNA Mutational Analysis Electronic Data Processing Sequence Analysis, DNA Algorithms Mutation Computer Simulation High-Throughput Nucleotide Sequencing Reproducibility of Results Neoplasms Humans Deep Learning Software Polymorphism, Single Nucleotide
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GPU-DAEMON: GPU algorithm design, data management & optimization template for array based big omics data.

Computers in biology and medicine Aug 16, 2018
In the age of ever increasing data, faster and more efficient data processing algorithms are needed. Graphics Processing Units (GPU) are emerging as a cost-effective alternative architecture for high-end computing. The optimal design of GPU algorithm...
Models, Theoretical Electronic Data Processing Machine Learning Big Data
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Evolutionary image simplification for lung nodule classification with convolutional neural networks.

International journal of computer assisted radiology and surgery May 29, 2018
PURPOSE: Understanding decisions of deep learning techniques is important. Especially in the medical field, the reasons for a decision in a classification task are as crucial as the pure classification results. In this article, we propose a new appro...
Lung Neoplasms Solitary Pulmonary Nodule Decision Making Electronic Data Processing Lung Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Software Algorithms Humans Neural Networks, Computer Machine Learning
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Complex overlapping concepts: An effective auditing methodology for families of similarly structured BioPortal ontologies.

Journal of biomedical informatics May 28, 2018
In previous research, we have demonstrated for a number of ontologies that structurally complex concepts (for different definitions of "complex") in an ontology are more likely to exhibit errors than other concepts. Thus, such complex concepts often ...
Electronic Data Processing Vocabulary, Controlled National Cancer Institute (U.S.) United States Systematized Nomenclature of Medicine Biological Ontologies
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Automated EEG-based screening of depression using deep convolutional neural network.

Computer methods and programs in biomedicine Apr 18, 2018
In recent years, advanced neurocomputing and machine learning techniques have been used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In this paper, a novel computer model is presented for EEG-based screening of de...
Machine Learning Algorithms Computer Simulation Reproducibility of Results Diagnosis, Computer-Assisted Depression Humans Neural Networks, Computer Electroencephalography Signal Processing, Computer-Assisted Electronic Data Processing
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