AIMC Topic: Semantics

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A Sentence-Level Joint Relation Classification Model Based on Reinforcement Learning.

Computational intelligence and neuroscience
Relation classification is an important semantic processing task in the field of natural language processing (NLP). Data sources generally adopt remote monitoring strategies to automatically generate large-scale training data, which inevitably causes...

An Examination of the Statistical Laws of Semantic Change in Clinical Notes.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Natural language is continually changing. Given the prevalence of unstructured, free-text clinical notes in the healthcare domain, understanding the aspects of this change is of critical importance to clinical Natural Language Processing (NLP) system...

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
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...

Soft and self constrained clustering for group-based labeling.

Medical image analysis
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 ...

Hybrid Pyramid Convolutional Network for Multiscale Face Detection.

Computational intelligence and neuroscience
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...

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
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...

Semantic segmentation of human oocyte images using deep neural networks.

Biomedical engineering online
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...

Augmented semantic feature based generative network for generalized zero-shot learning.

Neural networks : the official journal of the International Neural Network Society
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,...

A neuralized feature engineering method for entity relation extraction.

Neural networks : the official journal of the International Neural Network Society
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...

Establishing a consensus for the hallmarks of cancer based on gene ontology and pathway annotations.

BMC bioinformatics
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...