AIMC Topic: Humans

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A hybrid neural network for large-scale expressway network OD prediction based on toll data.

PloS one May 23, 2019
Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collec...
Motor Vehicles Models, Theoretical Data Interpretation, Statistical Humans Automobile Driving Neural Networks, Computer China
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Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one May 23, 2019
BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-...
Humans Area Under Curve Artificial Intelligence False Positive Reactions Colonic Neoplasms Machine Learning Oligonucleotide Array Sequence Analysis Nonlinear Dynamics Software Genetic Techniques Algorithms Computer Simulation Gene Expression Profiling Computational Biology
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Efficient Activity Recognition in Smart Homes Using Delayed Fuzzy Temporal Windows on Binary Sensors.

IEEE journal of biomedical and health informatics May 22, 2019
Human activity recognition has become an active research field over the past few years due to its wide application in various fields such as health-care, smart home monitoring, and surveillance. Existing approaches for activity recognition in smart h...
(1)
Human Activities Humans Neural Networks, Computer Fuzzy Logic
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Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network.

IEEE transactions on medical imaging May 22, 2019
Automatic and accurate classification of apoptosis, or programmed cell death, will facilitate cell biology research. The state-of-the-art approaches in apoptosis classification use deep convolutional neural networks (CNNs). However, these networks ar...
Humans Neural Networks, Computer Cell Line, Tumor Image Processing, Computer-Assisted Microscopy, Phase-Contrast Apoptosis Cytological Techniques Cells
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Deep residual network for off-resonance artifact correction with application to pediatric body MRA with 3D cones.

Magnetic resonance in medicine May 22, 2019
PURPOSE: To enable rapid imaging with a scan time-efficient 3D cones trajectory with a deep-learning off-resonance artifact correction technique.
Artifacts Magnetic Resonance Angiography Phantoms, Imaging Humans Child, Preschool Child Female Imaging, Three-Dimensional Pulmonary Veins Male Deep Learning
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Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

Dento maxillo facial radiology May 22, 2019
OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.
Sensitivity and Specificity Deep Learning Parotid Gland Sjogren's Syndrome Humans Tomography, X-Ray Computed
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Texture-Map-Based Branch-Collaborative Network for Oral Cancer Detection.

IEEE transactions on biomedical circuits and systems May 22, 2019
The paper proposes an innovative deep convolutional neural network (DCNN) combined with texture map for detecting cancerous regions and marking the ROI in a single model automatically. The proposed DCNN model contains two collaborative branches, name...
Mouth Neoplasms Wavelet Analysis Algorithms Image Processing, Computer-Assisted Early Detection of Cancer Humans Neural Networks, Computer
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Method for Identifying Cancer-Related Genes Using Gene Similarity-Based Collaborative Filtering.

Journal of computational biology : a journal of computational molecular cell biology May 22, 2019
Female Breast Neoplasms Biomarkers, Tumor RNA-Seq Humans Models, Genetic Machine Learning Genes, Neoplasm
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Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment May 22, 2019
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.
Microscopy Survival Analysis Tumor Burden Neoplasm Staging Neoplasm Grading Workflow Neoplasm Metastasis Immunohistochemistry Kaplan-Meier Estimate Adult Breast Neoplasms Biomarkers, Tumor Middle Aged Image Processing, Computer-Assisted Follow-Up Studies Female Aged Aged, 80 and over Humans Machine Learning Prognosis
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Automated OCT angiography image quality assessment using a deep learning algorithm.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie May 22, 2019
PURPOSE: To expedite and to standardize the process of image quality assessment in optical coherence tomography angiography (OCTA) using a specialized deep learning algorithm (DLA).
Humans Neural Networks, Computer Algorithms Fluorescein Angiography Tomography, Optical Coherence Retrospective Studies Fundus Oculi Retinal Vessels Reproducibility of Results Artifacts Deep Learning
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