AIMC Topic: Humans
Showing 65101 to 65110 of 95995 articles
Hierarchical sequence labeling for extracting BEL statements from biomedical literature.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Extracting relations between bio-entities from biomedical literature is often a challenging task and also an essential step towards biomedical knowledge expansion. The BioCreative community has organized a shared task to evaluate the robu...
On building a diabetes centric knowledge base via mining the web.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Diabetes has become one of the hot topics in life science researches. To support the analytical procedures, researchers and analysts expend a mass of labor cost to collect experimental data, which is also error-prone. To reduce the cost a...
Attention-based deep residual learning network for entity relation extraction in Chinese EMRs.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in...
Time-sensitive clinical concept embeddings learned from large electronic health records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do not consider temporal dependenc...
An ontological framework for the formalization, organization and usage of TCM-Knowledge.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: The traditional Chinese Medicine Language System (TCMLS) is a large-scale terminology system, developed from 2002 on by the Institute of Information of Traditional Chinese Medicine (IITCM). Until now, more than 120,000 concepts, 300,000 t...
Confidence resets reveal hierarchical adaptive learning in humans.
PLoS computational biology
Apr 9, 2019
Hierarchical processing is pervasive in the brain, but its computational significance for learning under uncertainty is disputed. On the one hand, hierarchical models provide an optimal framework and are becoming increasingly popular to study cogniti...
Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging.
Journal of healthcare engineering
Apr 9, 2019
Cluster of microcalcifications can be an early sign of breast cancer. In this paper, we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work, we used 283 mammo...
Classification of high dimensional biomedical data based on feature selection using redundant removal.
PloS one
Apr 9, 2019
High dimensional biomedical data contain tens of thousands of features, accurate and effective identification of the core features in these data can be used to assist diagnose related diseases. However, there are often a large number of irrelevant or...
A fuzzy causal relational mapping and rough set-based model for context-specific human error rate estimation.
International journal of occupational safety and ergonomics : JOSE
Apr 8, 2019
Safety is of paramount importance in high-risk systems. Safe and reliable operation of a system depends mainly on its key component, 'the human'. Human error is pivotal in an accident sequence and the rate of error is instrumental in the analysis of ...
Deep learning-based image restoration algorithm for coronary CT angiography.
European radiology
Apr 8, 2019
OBJECTIVES: The purpose of this study was to compare the image quality of coronary computed tomography angiography (CTA) subjected to deep learning-based image restoration (DLR) method with images subjected to hybrid iterative reconstruction (IR).
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