AIMC Topic: Natural Language Processing

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Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Psychiatry research
Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is th...

Structured pruning of recurrent neural networks through neuron selection.

Neural networks : the official journal of the International Neural Network Society
Recurrent neural networks (RNNs) have recently achieved remarkable successes in a number of applications. However, the huge sizes and computational burden of these models make it difficult for their deployment on edge devices. A practically effective...

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number of professional and uncommon...

Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text.

BMC medical informatics and decision making
BACKGROUND: To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and attributes. Here we present ...

A study of deep learning methods for de-identification of clinical notes in cross-institute settings.

BMC medical informatics and decision making
BACKGROUND: De-identification is a critical technology to facilitate the use of unstructured clinical text while protecting patient privacy and confidentiality. The clinical natural language processing (NLP) community has invested great efforts in de...

Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer's disease.

BMC medical informatics and decision making
BACKGROUND: Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful relationships between entities au...

Natural language processing for populating lung cancer clinical research data.

BMC medical informatics and decision making
BACKGROUND: Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics approaches. Since manual extra...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

Pharmacoepidemiology and drug safety
PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical notes, and to implement the algorithm at five health care systems in the Vaccine Safety Datalink.

Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks.

BMC bioinformatics
BACKGROUND: In recent years, deep learning methods have been applied to many natural language processing tasks to achieve state-of-the-art performance. However, in the biomedical domain, they have not out-performed supervised word sense disambiguatio...