AIMC Topic: Deep Learning

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Identifying floating plastic marine debris using a deep learning approach.

Environmental science and pollution research international Apr 18, 2019
Estimating the volume of macro-plastics which dot the world's oceans is one of the most pressing environmental concerns of our time. Prevailing methods for determining the amount of floating plastic debris, usually conducted manually, are time demand...
Deep Learning Environmental Monitoring Oceans and Seas Plastics Waste Products
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Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

Journal of the American Chemical Society Apr 18, 2019
The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging based photobleaching event counting is a new approach for protein stoichiometry determination under phy...
Fluorescence ErbB Receptors Deep Learning Single Molecule Imaging Fluorescent Dyes Humans Protein Structure, Quaternary HeLa Cells Algorithms Photobleaching DNA, Single-Stranded Carbocyanines
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Measuring social, environmental and health inequalities using deep learning and street imagery.

Scientific reports Apr 18, 2019
Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding ur...
Humans Health Status Disparities London Socioeconomic Factors Housing Income Social Problems Employment Neural Networks, Computer Crime Deep Learning Satellite Imagery Cities
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Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization.

Scientific reports Apr 18, 2019
Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-crafted algorithms or machine learning approaches such as support vector machines (SVMs) and convolutional neural networks (CNNs). Most deep neural net...
Support Vector Machine Radiography Tuberculosis Thorax Humans X-Rays Neural Networks, Computer Machine Learning Algorithms Databases, Factual Deep Learning Image Processing, Computer-Assisted
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Open-source pipeline for multi-class segmentation of the spinal cord with deep learning.

Magnetic resonance imaging Apr 17, 2019
This paper presents an open-source pipeline to train neural networks to segment structures of interest from MRI data. The pipeline is tailored towards homogeneous datasets and requires relatively low amounts of manual segmentations (few dozen, or les...
Callithrix Gray Matter Models, Animal White Matter Image Processing, Computer-Assisted Magnetic Resonance Imaging Spinal Cord Humans Neural Networks, Computer Animals Deep Learning
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Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist Apr 17, 2019
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...
Radiographic Image Interpretation, Computer-Assisted Female Male Humans Middle Aged ROC Curve Databases, Factual Lung Neural Networks, Computer Lung Neoplasms Retrospective Studies Algorithms Deep Learning Tomography, X-Ray Computed
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A novel ECG signal compression method using spindle convolutional auto-encoder.

Computer methods and programs in biomedicine Apr 17, 2019
BACKGROUND AND OBJECTIVES: With rapid development of telehealth system and cloud platform, traditional 12-ECG signals with high resolution generate heavy burdens in data storage and transmission. This problem is increasingly addressed with various EC...
Electrocardiography Humans Telemedicine Models, Statistical Software Stochastic Processes Signal Processing, Computer-Assisted Algorithms Data Compression Deep Learning
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Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.

PloS one Apr 17, 2019
Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic tumor in osteosarcoma, employing advances in histopathology digi...
Osteosarcoma Necrosis Datasets as Topic Humans Deep Learning Bone Neoplasms Bone and Bones Software ROC Curve Image Interpretation, Computer-Assisted Reproducibility of Results Support Vector Machine
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Deep Robust Framework for Protein Function Prediction Using Variable-Length Protein Sequences.

IEEE/ACM transactions on computational biology and bioinformatics Apr 16, 2019
The order of amino acids in a protein sequence enables the protein to acquire a conformation suitable for performing functions, thereby motivating the need to analyze these sequences for predicting functions. Although machine learning based approache...
Amino Acid Sequence Protein Conformation Sequence Analysis, Protein Computational Biology Proteins Discriminant Analysis Algorithms Deep Learning
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Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net.

IEEE transactions on medical imaging Apr 16, 2019
The segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions, and non-rigid geometrical features. To address these difficulties, we introduce a deep Q network (DQN) dr...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Pancreas Humans Algorithms Databases, Factual
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