AI Medical Compendium Topic:
Language

Clear Filters Showing 731 to 740 of 1291 articles

Qualifying Certainty in Radiology Reports through Deep Learning-Based Natural Language Processing.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Communication gaps exist between radiologists and referring physicians in conveying diagnostic certainty. We aimed to explore deep learning-based bidirectional contextual language models for automatically assessing diagnostic ...

English Grammar Detection Based on LSTM-CRF Machine Learning Model.

Computational intelligence and neuroscience
Deep learning and neural network have been widely used in the field of speech, vocabulary, text, pictures, and other information processing fields, which has achieved excellent research results. Neural network algorithm and prediction model were used...

Creating efficiencies in the extraction of data from randomized trials: a prospective evaluation of a machine learning and text mining tool.

BMC medical research methodology
BACKGROUND: Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We evaluated a machine learning and text mining tool's ability to (a) automatically extract data elements from randomized t...

Analysis of Color Language and Aesthetic Paradigm of Print Art Based on GB-BP Neural Network.

Computational intelligence and neuroscience
Color is the basic element of printmaking art creation and also an important medium for artists to express their emotions. In order to improve the understanding of the print by tourists, the research first carries out image analysis of different colo...

Aspect-based sentiment analysis with graph convolution over syntactic dependencies.

Artificial intelligence in medicine
Aspect-based sentiment analysis is a natural language processing task whose aim is to automatically classify the sentiment associated with a specific aspect of a written text. In this study, we propose a novel model for aspect-based sentiment analysi...

Medical code prediction via capsule networks and ICD knowledge.

BMC medical informatics and decision making
BACKGROUND: Clinical notes record the health status, clinical manifestations and other detailed information of each patient. The International Classification of Diseases (ICD) codes are important labels for electronic health records. Automatic medica...

CapsTM: capsule network for Chinese medical text matching.

BMC medical informatics and decision making
BACKGROUND: Text Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc....

Transformers-sklearn: a toolkit for medical language understanding with transformer-based models.

BMC medical informatics and decision making
BACKGROUND: Transformer is an attention-based architecture proven the state-of-the-art model in natural language processing (NLP). To reduce the difficulty of beginning to use transformer-based models in medical language understanding and expand the ...

Multiple Embeddings Enhanced Multi-Graph Neural Networks for Chinese Healthcare Named Entity Recognition.

IEEE journal of biomedical and health informatics
Named Entity Recognition (NER) is a natural language processing task for recognizing named entities in a given sentence. Chinese NER is difficult due to the lack of delimited spaces and conventional features for determining named entity boundaries an...

Automated Amharic News Categorization Using Deep Learning Models.

Computational intelligence and neuroscience
For decades, machine learning techniques have been used to process Amharic texts. The potential application of deep learning on Amharic document classification has not been exploited due to a lack of language resources. In this paper, we present a de...