AIMC Topic: Semantics

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Quantification of BERT Diagnosis Generalizability Across Medical Specialties Using Semantic Dataset Distance.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science May 17, 2021
Deep learning models in healthcare may fail to generalize on data from unseen corpora. Additionally, no quantitative metric exists to tell how existing models will perform on new data. Previous studies demonstrated that NLP models of medical notes ge...
Medicine Language Humans Deep Learning Semantics
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Soft and self constrained clustering for group-based labeling.

Medical image analysis May 12, 2021
When using deep neural networks in medical image classification tasks, it is mandatory to prepare a large-scale labeled image set, and this often requires significant effort by medical experts. One strategy to reduce the labeling cost is group-based ...
Humans Endoscopy Cluster Analysis Neural Networks, Computer Semantics
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Hybrid Pyramid Convolutional Network for Multiscale Face Detection.

Computational intelligence and neuroscience May 5, 2021
Face detection remains a challenging problem due to the high variability of scale and occlusion despite the strong representational power of deep convolutional neural networks and their implicit robustness. To handle hard face detection under extreme...
Neural Networks, Computer Algorithms Semantics Rotation
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Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation.

Neural networks : the official journal of the International Neural Network Society Apr 24, 2021
There has been an increased interest in high-level image-to-image translation to achieve semantic matching. Through a powerful translation model, we can efficiently synthesize high-quality images with diverse appearances while retaining semantic matc...
Image Processing, Computer-Assisted Semantics Goals Neural Networks, Computer
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Semantic segmentation of human oocyte images using deep neural networks.

Biomedical engineering online Apr 23, 2021
BACKGROUND: Infertility is a significant problem of humanity. In vitro fertilisation is one of the most effective and frequently applied ART methods. The effectiveness IVF depends on the assessment and selection of gametes and embryo with the highest...
Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Humans Semantics Oocytes
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Augmented semantic feature based generative network for generalized zero-shot learning.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2021
Zero-shot learning (ZSL) aims to recognize objects in images when no training data is available for the object classes. Under generalized zero-shot learning (GZSL) setting, the test objects belong to seen or unseen categories. In many recent studies,...
Semantics Learning Machine Learning
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A neuralized feature engineering method for entity relation extraction.

Neural networks : the official journal of the International Neural Network Society Apr 16, 2021
Making full use of semantic and structure information in a sentence is critical to support entity relation extraction. Neural networks use stacked neural layers to perform designated feature transformations and can automatically extract high-order ab...
Electronic Health Records Semantics Neural Networks, Computer
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Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations.

BMC bioinformatics Apr 6, 2021
BACKGROUND: The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-le...
Gene Ontology Neoplasms Molecular Sequence Annotation Humans Semantics Consensus
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A deep learning segmentation strategy that minimizes the amount of manually annotated images.

F1000Research Mar 30, 2021
Deep learning has revolutionized the automatic processing of images. While deep convolutional neural networks have demonstrated astonishing segmentation results for many biological objects acquired with microscopy, this technology's good performance ...
Image Processing, Computer-Assisted Cell Nucleus Semantics Humans Neural Networks, Computer Deep Learning
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KG2Vec: A node2vec-based vectorization model for knowledge graph.

PloS one Mar 30, 2021
Since the word2vec model was proposed, many researchers have vectorized the data in the research field based on it. In the field of social network, the Node2Vec model improved on the basis of word2vec can vectorize nodes and edges in social networks,...
Databases, Factual Models, Theoretical Deep Learning Humans Social Networking Computer Graphics Semantics Data Accuracy Information Services Pattern Recognition, Automated
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