AIMC Topic: Deep Learning

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Diagnosis using deep-learning artificial intelligence based on the endocytoscopic observation of the esophagus.

Esophagus : official journal of the Japan Esophageal Society Dec 13, 2018
BACKGROUND AND AIMS: The endocytoscopic system (ECS) helps in virtual realization of histology and can aid in confirming histological diagnosis in vivo. We propose replacing biopsy-based histology for esophageal squamous cell carcinoma (ESCC) by usin...
Esophagitis Esophagoscopy Deep Learning ROC Curve Gastroesophageal Reflux Esophageal Squamous Cell Carcinoma Esophageal Neoplasms Retrospective Studies Sensitivity and Specificity Humans Algorithms
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A hierarchical machine learning classification approach for secondary task identification from observed driving behavior data.

Accident; analysis and prevention Dec 13, 2018
According to NHTSA, more than 3477 people (including 551 non-occupants) were killed and 391,000 were injured due to distraction-related crashes in 2015. The distracted driving epidemic has long been under research to identify its impact on driving be...
Accidents, Traffic Text Messaging Behavior Observation Techniques Distracted Driving Humans Adult Male Cell Phone Female Deep Learning
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Recognition of Emotions Using Multichannel EEG Data and DBN-GC-Based Ensemble Deep Learning Framework.

Computational intelligence and neuroscience Dec 13, 2018
Fusing multichannel neurophysiological signals to recognize human emotion states becomes increasingly attractive. The conventional methods ignore the complementarity between time domain characteristics, frequency domain characteristics, and time-freq...
Emotions Humans Electroencephalography Deep Learning Arousal Algorithms Support Vector Machine
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Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning.

IEEE transactions on neural networks and learning systems Dec 12, 2018
Neural decoding, which aims to predict external visual stimuli information from evoked brain activities, plays an important role in understanding human visual system. Many existing methods are based on linear models, and most of them only focus on ei...
Brain Deep Learning Bayes Theorem Pattern Recognition, Automated Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Automatic quantification of the LV function and mass: A deep learning approach for cardiovascular MRI.

Computer methods and programs in biomedicine Dec 12, 2018
OBJECTIVE: This paper proposes a novel approach for automatic left ventricle (LV) quantification using convolutional neural networks (CNN).
Deep Learning Algorithms Ventricular Function, Left Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Neural Networks, Computer
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Improving palliative care with deep learning.

BMC medical informatics and decision making Dec 12, 2018
BACKGROUND: Access to palliative care is a key quality metric which most healthcare organizations strive to improve. The primary challenges to increasing palliative care access are a combination of physicians over-estimating patient prognoses, and a ...
Deep Learning Humans Patient Selection Prognosis Electronic Health Records Palliative Care Clinical Decision-Making
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Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy.

Physics in medicine and biology Dec 12, 2018
Deep inspiration breath hold (DIBH) with surface supervising is a common technique for cardiac dose reduction in left breast cancer radiotherapy. Surface supervision accuracy relies on the characteristics of surface region. In this study, a convoluti...
Humans Female Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Breath Holding Monitoring, Physiologic Organs at Risk Unilateral Breast Neoplasms
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Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography.

Oral radiology Dec 11, 2018
OBJECTIVES: To apply a deep-learning system for diagnosis of maxillary sinusitis on panoramic radiography, and to clarify its diagnostic performance.
Area Under Curve Radiography, Panoramic Maxillary Sinusitis Neural Networks, Computer Humans Deep Learning
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Extending 2-D Convolutional Neural Networks to 3-D for Advancing Deep Learning Cancer Classification With Application to MRI Liver Tumor Differentiation.

IEEE journal of biomedical and health informatics Dec 11, 2018
Deep learning (DL) architectures have opened new horizons in medical image analysis attaining unprecedented performance in tasks such as tissue classification and segmentation as well as prediction of several clinical outcomes. In this paper, we prop...
Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Deep Learning Liver Neoplasms Humans Imaging, Three-Dimensional Neural Networks, Computer
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The Dawn of a New Era in Low-Dose PET Imaging.

Radiology Dec 11, 2018
Aniline Compounds Positron-Emission Tomography Stilbenes Deep Learning Magnetic Resonance Imaging
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