AIMC Topic: Natural Language Processing

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Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.

International journal of medical informatics
BACKGROUND: The management of hypertrophic cardiomyopathy (HCM) patients requires the knowledge of risk factors associated with sudden cardiac death (SCD). SCD risk factors such as syncope and family history of SCD (FH-SCD) as well as family history ...

BioWordVec, improving biomedical word embeddings with subword information and MeSH.

Scientific data
Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlab...

Classification of Patients with Coronary Microvascular Dysfunction.

IEEE/ACM transactions on computational biology and bioinformatics
While coronary microvascular dysfunction (CMD) is a major cause of ischemia, it is very challenging to diagnose due to lack of CMD-specific screening measures. CMD has been identified as one of the five priority areas of investigation in a 2014 Natio...

Recurrent neural networks with segment attention and entity description for relation extraction from clinical texts.

Artificial intelligence in medicine
At present, great progress has been achieved on the relation extraction for clinical texts, but we have noticed that the current models have great drawbacks when dealing with long sentences and multiple entities in a sentence. In this paper, we propo...

A Novel Memory-Scheduling Strategy for Large Convolutional Neural Network on Memory-Limited Devices.

Computational intelligence and neuroscience
Recently, machine learning, especially deep learning, has been a core algorithm to be widely used in many fields such as natural language processing, speech recognition, object recognition, and so on. At the same time, another trend is that more and ...

Developing a Physical Activity Ontology to Support the Interoperability of Physical Activity Data.

Journal of medical Internet research
BACKGROUND: Physical activity data provides important information on disease onset, progression, and treatment outcomes. Although analyzing physical activity data in conjunction with other clinical and microbiological data will lead to new insights c...

Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.

Journal of biomedical informatics
OBJECTIVE: Clinical care guidelines recommend that newly diagnosed prostate cancer patients at high risk for metastatic spread receive a bone scan prior to treatment and that low risk patients not receive it. The objective was to develop an automated...

Concept embedding to measure semantic relatedness for biomedical information ontologies.

Journal of biomedical informatics
There have been many attempts to identify relationships among concepts corresponding to terms from biomedical information ontologies such as the Unified Medical Language System (UMLS). In particular, vector representation of such concepts using infor...

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

International journal of medical informatics
OBJECTIVE: Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccination. Previous vaccine safety studies used non-specific diagnosis codes to identify potential local rea...

Cimind: A phonetic-based tool for multilingual named entity recognition in biomedical texts.

Journal of biomedical informatics
BACKGROUND: Extracting concepts from biomedical texts is a key to support many advanced applications such as biomedical information retrieval. However, in clinical notes Named Entity Recognition (NER) has to deal with various types of errors such as ...