AIMC Topic: Language

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Multimodal Sensor-Input Architecture with Deep Learning for Audio-Visual Speech Recognition in Wild.

Sensors (Basel, Switzerland)
This paper investigates multimodal sensor architectures with deep learning for audio-visual speech recognition, focusing on in-the-wild scenarios. The term "in the wild" is used to describe AVSR for unconstrained natural-language audio streams and vi...

Extracting medication changes in clinical narratives using pre-trained language models.

Journal of biomedical informatics
An accurate and detailed account of patient medications, including medication changes within the patient timeline, is essential for healthcare providers to provide appropriate patient care. Healthcare providers or the patients themselves may initiate...

Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning.

Sensors (Basel, Switzerland)
Digital twins have revolutionized manufacturing and maintenance, allowing us to interact with virtual yet realistic representations of the physical world in simulations to identify potential problems or opportunities for improvement. However, traditi...

Noise Reduction Learning Based on XLNet-CRF for Biomedical Named Entity Recognition.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, Biomedical Named Entity Recognition (BioNER) systems have mainly been based on deep neural networks, which are used to extract information from the rapidly expanding biomedical literature. Long-distance context autoencoding language ...

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...