AIMC Topic: Pattern Recognition, Automated
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Construction of Genealogical Knowledge Graphs From Obituaries: Multitask Neural Network Extraction System.
Journal of medical Internet research
Aug 4, 2021
BACKGROUND: Genealogical information, such as that found in family trees, is imperative for biomedical research such as disease heritability and risk prediction. Researchers have used policyholder and their dependent information in medical claims dat...
EHR-Oriented Knowledge Graph System: Toward Efficient Utilization of Non-Used Information Buried in Routine Clinical Practice.
IEEE journal of biomedical and health informatics
Jul 27, 2021
Non-used clinical information has negative implications on healthcare quality. Clinicians pay priority attention to clinical information relevant to their specialties during routine clinical practices but may be insensitive or less concerned about in...
Disease ontologies for knowledge graphs.
BMC bioinformatics
Jul 21, 2021
BACKGROUND: Data integration to build a biomedical knowledge graph is a challenging task. There are multiple disease ontologies used in data sources and publications, each having its hierarchy. A common task is to map between ontologies, find disease...
An empirical survey of data augmentation for time series classification with neural networks.
PloS one
Jul 15, 2021
In recent times, deep artificial neural networks have achieved many successes in pattern recognition. Part of this success can be attributed to the reliance on big data to increase generalization. However, in the field of time series recognition, man...
Time-Frequency Representation and Convolutional Neural Network-Based Emotion Recognition.
IEEE transactions on neural networks and learning systems
Jul 6, 2021
Emotions composed of cognizant logical reactions toward various situations. Such mental responses stem from physiological, cognitive, and behavioral changes. Electroencephalogram (EEG) signals provide a noninvasive and nonradioactive solution for emo...
Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization.
IEEE transactions on pattern analysis and machine intelligence
Jul 1, 2021
Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potential for improving representation and generalization abilities of deep C...
Toward a Coronavirus Knowledge Graph.
Genes
Jun 29, 2021
This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a col...
Abstraction and analogy-making in artificial intelligence.
Annals of the New York Academy of Sciences
Jun 25, 2021
Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite a long history of research on constructing artificial intelligence (AI) systems with...
Using distance on the Riemannian manifold to compare representations in brain and in models.
NeuroImage
Jun 19, 2021
Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner ...
Robotic Applications in Orthodontics: Changing the Face of Contemporary Clinical Care.
BioMed research international
Jun 16, 2021
The last decade (2010-2021) has witnessed the evolution of robotic applications in orthodontics. This review scopes and analyzes published orthodontic literature in eight different domains: (1) robotic dental assistants; (2) robotics in diagnosis and...
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