AIMC Topic:
Databases, Factual
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An automated data verification approach for improving data quality in a clinical registry.
Computer methods and programs in biomedicine
Jan 31, 2019
BACKGROUND AND OBJECTIVE: The quality of data is crucial for clinical registry studies as it impacts credibility. In the regular practice of most such studies, a vulnerability arises from researchers recording data on paper-based case report forms (C...
Automation
Pattern Recognition, Automated
Databases, Factual
Humans
Electronic Health Records
Machine Learning
Language
Algorithms
Reproducibility of Results
Programming Languages
Data Accuracy
Information Storage and Retrieval
Medical Informatics
Regression Analysis
Natural Language Processing
Registries
Coronary Artery Disease
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 31, 2019
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of electromyography-based gesture reco...
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 31, 2019
Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography epochs one at a time. In this paper, we tackle the task as a sequence-to-sequence classification...
Pulmonary nodule segmentation with CT sample synthesis using adversarial networks.
Medical physics
Jan 31, 2019
PURPOSE: Segmentation of pulmonary nodules is critical for the analysis of nodules and lung cancer diagnosis. We present a novel framework of segmentation for various types of nodules using convolutional neural networks (CNNs).
Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages.
Scientific reports
Jan 31, 2019
High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative prognosis for this cohort can lead to better treatment planning. Conventional survival prediction based on clinical information is subjective and could be inacc...
Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network.
AJR. American journal of roentgenology
Jan 30, 2019
OBJECTIVE: Radiology reports are rich resources for biomedical researchers. Before utilization of radiology reports, experts must manually review these reports to identify the categories. In fact, automatically categorizing electronic medical record ...
Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Prediction of mortality following pediatric heart transplant using machine learning algorithms.
Pediatric transplantation
Jan 29, 2019
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes ...
Features Combined From Hundreds of Midlayers: Hierarchical Networks With Subnetwork Nodes.
IEEE transactions on neural networks and learning systems
Jan 28, 2019
In this paper, we believe that the mixed selectivity of neuron in the top layer encodes distributed information produced from other neurons to offer a significant computational advantage over recognition accuracy. Thus, this paper proposes a hierarch...
RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 26, 2019
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and other mental functions. Magnetic resonance images (MRI) have been widely used as an important imaging modality of brain for AD diagnosis ...
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