AIMC Topic: Natural Language Processing

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Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts.

Computers in biology and medicine
BACKGROUND: This study demonstrates clinical named entity recognition (NER) methods on the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the adoption rate of the electronic health record (EHR) system in global h...

How Concrete Do We Get Telling Stories?

Topics in cognitive science
Will reading different stories about the same event in the world result in a similar image of the world? Will reading the same story by different people result in a similar proxy for experiencing the story? The answer to both questions is no because ...

Normalizing Spontaneous Reports Into MedDRA: Some Experiments With MagiCoder.

IEEE journal of biomedical and health informatics
Text normalization into medical dictionaries is useful to support clinical tasks. A typical setting is pharmacovigilance (PV). The manual detection of suspected adverse drug reactions (ADRs) in narrative reports is time consuming and natural language...

Autonomous detection, grading, and reporting of postoperative complications using natural language processing.

Surgery
INTRODUCTION: Natural language processing, a computer science technique that allows interpretation of narrative text, is infrequently used to identify surgical complications. We designed a natural language processing algorithm to identify and grade t...

Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training.

PloS one
This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input contexts of different length in or...

Biomedical literature classification with a CNNs-based hybrid learning network.

PloS one
Deep learning techniques, e.g., Convolutional Neural Networks (CNNs), have been explosively applied to the research in the fields of information retrieval and natural language processing. However, few research efforts have addressed semantic indexing...

Discovering and identifying New York heart association classification from electronic health records.

BMC medical informatics and decision making
BACKGROUND: Cardiac Resynchronization Therapy (CRT) is an established pacing therapy for heart failure patients. The New York Heart Association (NYHA) class is often used as a measure of a patient's response to CRT. Identifying NYHA class for heart f...

Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases.

BMC medical informatics and decision making
BACKGROUND: In the past few years, neural word embeddings have been widely used in text mining. However, the vector representations of word embeddings mostly act as a black box in downstream applications using them, thereby limiting their interpretab...

Using natural language processing methods to classify use status of dietary supplements in clinical notes.

BMC medical informatics and decision making
BACKGROUND: Despite widespread use, the safety of dietary supplements is open to doubt due to the fact that they can interact with prescribed medications, leading to dangerous clinical outcomes. Electronic health records (EHRs) provide a potential wa...

Automatic extraction of protein-protein interactions using grammatical relationship graph.

BMC medical informatics and decision making
BACKGROUND: Relationships between bio-entities (genes, proteins, diseases, etc.) constitute a significant part of our knowledge. Most of this information is documented as unstructured text in different forms, such as books, articles and on-line pages...