Protein engineering through machine-learning-guided directed evolution enables the optimization of protein functions. Machine-learning approaches predict how sequence maps to function in a data-driven manner without requiring a detailed model of the ...
Improperly grown trees may cause huge hazards to the environment and to humans, through e.g., climate change, soil erosion, etc. A proximity environmental feature-based tree health assessment (PTA) scheme is proposed to prevent these hazards by provi...
Heart failure with preserved ejection fraction (HFpEF) is a complex and heterogeneous clinical syndrome. For the purpose of assisting HFpEF diagnosis, a non-invasive method using extreme learning machine and heart sound (HS) characteristics was provi...
Computational intelligence and neuroscience
Jul 14, 2019
Relation extraction is the underlying critical task of textual understanding. However, the existing methods currently have defects in instance selection and lack background knowledge for entity recognition. In this paper, we propose a knowledge-based...
Computational intelligence and neuroscience
Jul 14, 2019
The threat to people's lives and property posed by fires has become increasingly serious. To address the problem of a high false alarm rate in traditional fire detection, an innovative detection method based on multifeature fusion of flame is propose...
As the incidence of senile dementia continues to increase, researches on Alzheimer's disease (AD) have become more and more important. Several studies have reported that there is a close relationship between AD and aging. Some researchers even pointe...
BACKGROUND/AIMS: To develop a deep learning system (DLS) that can automatically detect malignant melanoma (MM) in the eyelid from histopathological sections with colossal information density.
Journal of the American College of Surgeons
Jul 13, 2019
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and earlier models include data not available at the time of scheduling. Our objective was to develop stat...
Classical deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimization problem for each image pair. Recently, learning-based methods have ...
Accurate segmentation of the left ventricle (LV) from cine magnetic resonance imaging (MRI) is an important step in the reliable assessment of cardiac function in cardiovascular disease patients. Several deep learning convolutional neural network (CN...
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