AI Medical Compendium Topic:
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Knowledge Guided Attention and Graph Convolutional Networks for Chemical-Disease Relation Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
The automatic extraction of the chemical-disease relation (CDR) from the text becomes critical because it takes a lot of time and effort to extract valuable CDR manually. Studies have shown that prior knowledge from the biomedical knowledge base is i...

MedLexSp - a medical lexicon for Spanish medical natural language processing.

Journal of biomedical semantics
BACKGROUND: Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, lemmatization or natural language genera...

Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis.

Journal of medical Internet research
BACKGROUND: The evolution of artificial intelligence and natural language processing generates new opportunities for conversational agents (CAs) that communicate and interact with individuals. In the health domain, CAs became popular as they allow fo...

The ecological discourse analysis of news discourse based on deep learning from the perspective of ecological philosophy.

PloS one
Recently, ecological damage and environmental pollution have become increasingly serious. Experts in various fields have started to study related issues from diverse points of view. To prevent the accelerated deterioration of the ecological environme...

CARES: A Corpus for classification of Spanish Radiological reports.

Computers in biology and medicine
This paper presents a new corpus of radiology medical reports written in Spanish and labeled with ICD-10. CARES (Corpus of Anonymised Radiological Evidences in Spanish) is a high-quality corpus manually labeled and reviewed by radiologists that is fr...

Transformer-based deep learning for predicting protein properties in the life sciences.

eLife
Recent developments in deep learning, coupled with an increasing number of sequenced proteins, have led to a breakthrough in life science applications, in particular in protein property prediction. There is hope that deep learning can close the gap b...

Diversity Learning Based on Multi-Latent Space for Medical Image Visual Question Generation.

Sensors (Basel, Switzerland)
Auxiliary clinical diagnosis has been researched to solve unevenly and insufficiently distributed clinical resources. However, auxiliary diagnosis is still dominated by human physicians, and how to make intelligent systems more involved in the diagno...

A Chinese verb semantic feature dataset (CVFD).

Behavior research methods
Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets...

A Lightweight Sentiment Analysis Framework for a Micro-Intelligent Terminal.

Sensors (Basel, Switzerland)
Sentiment analysis aims to mine polarity features in the text, which can empower intelligent terminals to recognize opinions and further enhance interaction capabilities with customers. Considerable progress has been made using recurrent neural netwo...

TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification.

IEEE transactions on neural networks and learning systems
Sentiment classification is a form of data analytics where people's feelings and attitudes toward a topic are mined from data. This tantalizing power to "predict the zeitgeist" means that sentiment classification has long attracted interest, but with...