IEEE journal of biomedical and health informatics
Sep 24, 2019
Thrombotic events are one of the leading causes of mortality and morbidity related to cancer, with ovarian cancer having one of the highest incidence rates. The need to prevent these events through the prescription of adequate schemes of antithrombot...
Background and Purpose- The availability of and expertise to interpret advanced neuroimaging recommended in the guideline-based endovascular stroke therapy (EST) evaluation are limited. Here, we develop and validate an automated machine learning-base...
IEEE journal of biomedical and health informatics
Sep 23, 2019
Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. However, recent researches show that a well-trained deep learning model may not generalize well to data from different cohorts due to domain shift. Sim...
Journal of cardiovascular computed tomography
Sep 23, 2019
BACKGROUND: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to exam...
The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to ...
Created in October 2012, Wikidata is a large-scale, human-readable, machine-readable, multilingual, multidisciplinary, centralized, editable, structured, and linked knowledge-base with an increasing diversity of use cases. Here, we raise awareness of...
Proceedings of the National Academy of Sciences of the United States of America
Sep 16, 2019
The expansion of machine learning to high-stakes application domains such as medicine, finance, and criminal justice, where making informed decisions requires clear understanding of the model, has increased the interest in interpretable machine learn...
Journal of medical engineering & technology
Sep 10, 2019
This paper presents an advanced approach for foetal brain abnormalities diagnostic by integrating significant biometric features in the identification process. In foetal anomaly diagnosis, manual evaluation of foetal behaviour in ultrasound images is...
IEEE transactions on neural networks and learning systems
Sep 9, 2019
Group convolution is widely used in many mobile networks to remove the filter's redundancy from the channel extent. In order to further reduce the redundancy of group convolution, this article proposes a novel repeated group convolutional (RGC) kerne...
Epilepsy is the most common neurological disorder in humans. Electroencephalogram is a prevalent tool for diagnosing the epileptic seizure activity in clinical, which provides valuable information for understanding the physiological mechanisms behind...
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