AIMC Topic: Natural Language Processing

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Leveraging Semantics in WordNet to Facilitate the Computer-Assisted Coding of ICD-11.

IEEE journal of biomedical and health informatics
The International Classification of Diseases (ICD) not only serves as the bedrock for health statistics but also provides a holistic overview of every health aspect of life. This study aims to facilitate the computer-assisted coding of the 11th revis...

Ensembles of natural language processing systems for portable phenotyping solutions.

Journal of biomedical informatics
BACKGROUND: Manually curating standardized phenotypic concepts such as Human Phenotype Ontology (HPO) terms from narrative text in electronic health records (EHRs) is time consuming and error prone. Natural language processing (NLP) techniques can fa...

Associative attention networks for temporal relation extraction from electronic health records.

Journal of biomedical informatics
Temporal relations are crucial in constructing a timeline over the course of clinical care, which can help medical practitioners and researchers track the progression of diseases, treatments and adverse reactions over time. Due to the rapid adoption ...

RedMed: Extending drug lexicons for social media applications.

Journal of biomedical informatics
Social media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data has been hindered by the massive and noisy nature of the data. Initial attempts to use social media data have rel...

Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.

Journal of biomedical informatics
OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concepts in clinical notes on the example of decline of insulin therapy recommendation by patients.

A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis.

International journal of medical informatics
CONTEXT: Adverse events in healthcare are often collated in incident reports which contain unstructured free text. Learning from these events may improve patient safety. Natural language processing (NLP) uses computational techniques to interrogate f...

Deep contextualized embeddings for quantifying the informative content in biomedical text summarization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Capturing the context of text is a challenging task in biomedical text summarization. The objective of this research is to show how contextualized embeddings produced by a deep bidirectional language model can be utilized to...

A frame semantic overview of NLP-based information extraction for cancer-related EHR notes.

Journal of biomedical informatics
OBJECTIVE: There is a lot of information about cancer in Electronic Health Record (EHR) notes that can be useful for biomedical research provided natural language processing (NLP) methods are available to extract and structure this information. In th...

Extracting comprehensive clinical information for breast cancer using deep learning methods.

International journal of medical informatics
OBJECTIVE: Breast cancer is the most common malignant tumor among women. The diagnosis and treatment information of breast cancer patients is abundant in multiple types of clinical fields, including clinicopathological data, genotype and phenotype in...

Use of Natural Language Processing to identify Obsessive Compulsive Symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder.

Scientific reports
Obsessive and Compulsive Symptoms (OCS) or Obsessive Compulsive Disorder (OCD) in the context of schizophrenia or related disorders are of clinical importance as these are associated with a range of adverse outcomes. Natural Language Processing (NLP)...