AIMC Topic: Natural Language Processing

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The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings.

Computers in biology and medicine
BACKGROUND: Word vectors or word embeddings are n-dimensional representations of words and form the backbone of Natural Language Processing of textual data. This research experiments with algorithms that augment word vectors with lexical constraints ...

5335 days of Implementation Science: using natural language processing to examine publication trends and topics.

Implementation science : IS
INTRODUCTION: Moving evidence-based practices into the hands of practitioners requires the synthesis and translation of research literature. However, the growing pace of scientific publications across disciplines makes it increasingly difficult to st...

Extracting knowledge networks from plant scientific literature: potato tuber flesh color as an exemplary trait.

BMC plant biology
BACKGROUND: Scientific literature carries a wealth of information crucial for research, but only a fraction of it is present as structured information in databases and therefore can be analyzed using traditional data analysis tools. Natural language ...

Contextual embedding bootstrapped neural network for medical information extraction of coronary artery disease records.

Medical & biological engineering & computing
Coronary artery disease (CAD) is the major cause of human death worldwide. The development of new CAD early diagnosis methods based on medical big data has a great potential to reduce the risk of CAD death. In this process, neural network (NN), as a ...

Vision-Language-Knowledge Co-Embedding for Visual Commonsense Reasoning.

Sensors (Basel, Switzerland)
Visual commonsense reasoning is an intelligent task performed to decide the most appropriate answer to a question while providing the rationale or reason for the answer when an image, a natural language question, and candidate responses are given. Fo...

Healthfulness Assessment of Recipes Shared on Pinterest: Natural Language Processing and Content Analysis.

Journal of medical Internet research
BACKGROUND: Although Pinterest has become a popular platform for distributing influential information that shapes users' behaviors, the role of recipes pinned on Pinterest in these behaviors is not well understood.

Review of Temporal Reasoning in the Clinical Domain for Timeline Extraction: Where we are and where we need to be.

Journal of biomedical informatics
Understanding a patient's medical history, such as how long symptoms last or when a procedure was performed, is vital to diagnosing problems and providing good care. Frequently, important information regarding a patient's medical timeline is buried i...

G2Basy: A framework to improve the RNN language model and ease overfitting problem.

PloS one
Recurrent neural networks are efficient ways of training language models, and various RNN networks have been proposed to improve performance. However, with the increase of network scales, the overfitting problem becomes more urgent. In this paper, we...

Subsentence Extraction from Text Using Coverage-Based Deep Learning Language Models.

Sensors (Basel, Switzerland)
Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience, and computer science. This stems from its high degree of subjectivity and limited input sources that can effectively captur...

Pseudotext Injection and Advance Filtering of Low-Resource Corpus for Neural Machine Translation.

Computational intelligence and neuroscience
Scaling natural language processing (NLP) to low-resourced languages to improve machine translation (MT) performance remains enigmatic. This research contributes to the domain on a low-resource English-Twi translation based on filtered synthetic-para...