AIMC Topic: Natural Language Processing

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Visualizing patient journals by combining vital signs monitoring and natural language processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a data-driven approach to graphically presenting text-based patient journals while still maintaining all textual information. The system first creates a timeline representation of a patients' physiological condition during an admi...

Natural Language Processing in Oncology: A Review.

JAMA oncology
IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest important cl...

Text-Attentional Convolutional Neural Network for Scene Text Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature globally computed from a whole image component (patch), where the cluttered background...

Natural Language Processing in Radiology: A Systematic Review.

Radiology
Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are st...

Unsupervised Topic Modeling in a Large Free Text Radiology Report Repository.

Journal of digital imaging
Radiology report narrative contains a large amount of information about the patient's health and the radiologist's interpretation of medical findings. Most of this critical information is entered in free text format, even when structured radiology re...

[Short Text Classification of EMR Based on Entities and Dependency Parser].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Nowadays, text classification and text mining of Electronic Medical Record (EMR) have become the basis of the Big Data research in biomedical fields. This paper proposes a method using entity dictionaries and dependency parser as the feature to do th...

Probability Statements Extraction with Constrained Conditional Random Fields.

Studies in health technology and informatics
This paper investigates how to extract probability statements from academic medical papers. In previous work we have explored traditional classification methods which led to numerous false negatives. This current work focuses on constraining classifi...

Suggesting Missing Relations in Biomedical Ontologies Based on Lexical Regularities.

Studies in health technology and informatics
The number of biomedical ontologies has increased significantly in recent years. Many of such ontologies are the result of efforts of communities of domain experts and ontology engineers. The development and application of quality assurance (QA) meth...

Natural language processing and the Now-or-Never bottleneck.

The Behavioral and brain sciences
Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Neve...