AIMC Topic: Natural Language Processing

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Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text.

Yearbook of medical informatics
Natural Language Processing (NLP) methods are increasingly being utilized to mine knowledge from unstructured health-related texts. Recent advances in noisy text processing techniques are enabling researchers and medical domain experts to go beyond ...

Learning from Narrated Instruction Videos.

IEEE transactions on pattern analysis and machine intelligence
Automatic assistants could guide a person or a robot in performing new tasks, such as changing a car tire or repotting a plant. Creating such assistants, however, is non-trivial and requires understanding of visual and verbal content of a video. Towa...

Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews.

Journal of healthcare engineering
Adverse drug reactions (ADRs) are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. T...

Machine Learning Approaches on Diagnostic Term Encoding With the ICD for Clinical Documentation.

IEEE journal of biomedical and health informatics
This work focuses on data mining applied to the clinical documentation domain. Diagnostic terms (DTs) are used as keywords to retrieve valuable information from electronic health records. Indeed, they are encoded manually by experts following the Int...

Word2Vec inversion and traditional text classifiers for phenotyping lupus.

BMC medical informatics and decision making
BACKGROUND: Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text cl...

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Methods of information in medicine
OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural langua...

Decoding naturalistic experiences from human brain activity via distributed representations of words.

NeuroImage
Natural visual scenes induce rich perceptual experiences that are highly diverse from scene to scene and from person to person. Here, we propose a new framework for decoding such experiences using a distributed representation of words. We used functi...

Developing a cardiovascular disease risk factor annotated corpus of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular disease (CVD) has become the leading cause of death in China, and most of the cases can be prevented by controlling risk factors. The goal of this study was to build a corpus of CVD risk factor annotations based on Chinese ...

Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation.

Journal of biomedical informatics
Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorith...