AIMC Topic: Natural Language Processing

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Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: We implement 2 different multitask learning (MTL) techniques, hard parameter sharing and cross-stitch, to train a word-level convolutional neural network (CNN) specifically designed for automatic extraction of cancer data from unstructured...
Support Vector Machine Machine Learning Information Storage and Retrieval Natural Language Processing Neoplasms Humans Registries Neural Networks, Computer
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Supporting the use of standardized nursing terminologies with automatic subject heading prediction: a comparison of sentence-level text classification methods.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This study focuses on the task of automatically assigning standardized (topical) subject headings to free-text sentences in clinical nursing notes. The underlying motivation is to support nurses when they document patient care by developin...
Electronic Health Records Standardized Nursing Terminology Abstracting and Indexing Natural Language Processing Subject Headings Finland Nursing Records
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Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: Detecting adverse drug events (ADEs) and medications related information in clinical notes is important for both hospital medical care and medical research. We describe our clinical natural language processing (NLP) system to automatically...
Unified Medical Language System Drug-Related Side Effects and Adverse Reactions Knowledge Bases Information Storage and Retrieval Narration Natural Language Processing Neural Networks, Computer Electronic Health Records Deep Learning Humans
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2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This article summarizes the preparation, organization, evaluation, and results of Track 2 of the 2018 National NLP Clinical Challenges shared task. Track 2 focused on extraction of adverse drug events (ADEs) from clinical records and evalu...
Humans Deep Learning Support Vector Machine Electronic Health Records Datasets as Topic Natural Language Processing Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval Patient Discharge Summaries
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Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: To develop a natural language processing system that identifies relations of medications with adverse drug events from clinical narratives. This project is part of the 2018 n2c2 challenge.
Information Storage and Retrieval Natural Language Processing Drug-Related Side Effects and Adverse Reactions Humans Neural Networks, Computer Electronic Health Records Deep Learning Narration
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Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: Identification of drugs, associated medication entities, and interactions among them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events. This article describes our participation to the n2c2 shared-task in...
Information Storage and Retrieval Electronic Health Records Deep Learning Drug Interactions Drug-Related Side Effects and Adverse Reactions Natural Language Processing Humans Neural Networks, Computer
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Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: An adverse drug event (ADE) refers to an injury resulting from medical intervention related to a drug including harm caused by drugs or from the usage of drugs. Extracting ADEs from clinical records can help physicians associate adverse ev...
Neural Networks, Computer Algorithms Electronic Health Records Humans Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval Terminology as Topic Narration Natural Language Processing
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Ensemble method-based extraction of medication and related information from clinical texts.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: Accurate and complete information about medications and related information is crucial for effective clinical decision support and precise health care. Recognition and reduction of adverse drug events is also central to effective patient c...
Electronic Health Records Narration Natural Language Processing Humans Algorithms Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval
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CoCoScore: context-aware co-occurrence scoring for text mining applications using distant supervision.

Bioinformatics (Oxford, England) Jan 1, 2020
MOTIVATION: Information extraction by mining the scientific literature is key to uncovering relations between biomedical entities. Most existing approaches based on natural language processing extract relations from single sentence-level co-mentions,...
Computational Biology Data Mining Natural Language Processing Proteins Publications Humans
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An ensemble of neural models for nested adverse drug events and medication extraction with subwords.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This article describes an ensembling system to automatically extract adverse drug events and drug related entities from clinical narratives, which was developed for the 2018 n2c2 Shared Task Track 2.
Humans Neural Networks, Computer Natural Language Processing Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval Electronic Health Records Narration
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