AI Medical Compendium Topic:
Semantics

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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...

A deep learning segmentation strategy that minimizes the amount of manually annotated images.

F1000Research
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 ...

KG2Vec: A node2vec-based vectorization model for knowledge graph.

PloS one
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,...

Enhancement of Target-Oriented Opinion Words Extraction with Multiview-Trained Machine Reading Comprehension Model.

Computational intelligence and neuroscience
Target-oriented opinion words extraction (TOWE) seeks to identify opinion expressions oriented to a specific target, and it is a crucial step toward fine-grained opinion mining. Recent neural networks have achieved significant success in this task by...

SIENA: Semi-automatic semantic enhancement of datasets using concept recognition.

Journal of biomedical semantics
BACKGROUND: The amount of available data, which can facilitate answering scientific research questions, is growing. However, the different formats of published data are expanding as well, creating a serious challenge when multiple datasets need to be...

Protocol for a reproducible experimental survey on biomedical sentence similarity.

PloS one
Measuring semantic similarity between sentences is a significant task in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and biomedical text mining. For this reason, the proposal of sentence similarity methods for the bio...

Deep Artificial Neural Networks Reveal a Distributed Cortical Network Encoding Propositional Sentence-Level Meaning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Understanding how and where in the brain sentence-level meaning is constructed from words presents a major scientific challenge. Recent advances have begun to explain brain activation elicited by sentences using vector models of word meaning derived ...