AIMC Topic: Information Storage and Retrieval

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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.
Humans Neural Networks, Computer Narration Natural Language Processing Information Storage and Retrieval Electronic Health Records Drug-Related Side Effects and Adverse Reactions Deep Learning
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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 Drug Interactions Drug-Related Side Effects and Adverse Reactions Humans Neural Networks, Computer Deep Learning Natural Language Processing Electronic Health Records
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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...
Information Storage and Retrieval Terminology as Topic Algorithms Electronic Health Records Natural Language Processing Drug-Related Side Effects and Adverse Reactions Humans Neural Networks, Computer Narration
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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...
Humans Algorithms Electronic Health Records Information Storage and Retrieval Natural Language Processing Drug-Related Side Effects and Adverse Reactions Narration
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Towards reliable named entity recognition in the biomedical domain.

Bioinformatics (Oxford, England) Jan 1, 2020
MOTIVATION: Automatic biomedical named entity recognition (BioNER) is a key task in biomedical information extraction. For some time, state-of-the-art BioNER has been dominated by machine learning methods, particularly conditional random fields (CRFs...
Machine Learning Software Models, Genetic Deep Learning Information Storage and Retrieval Computational Biology
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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.
Information Storage and Retrieval Neural Networks, Computer Electronic Health Records Natural Language Processing Narration Humans Drug-Related Side Effects and Adverse Reactions
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A study of deep learning approaches for medication and adverse drug event extraction from clinical text.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2020
OBJECTIVE: This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National NLP Clinical Challenges (n2c2) shared task.
Machine Learning Algorithms Electronic Health Records Humans Pharmaceutical Preparations Drug-Related Side Effects and Adverse Reactions Information Storage and Retrieval Narration Natural Language Processing Deep Learning
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Transparent Reporting on Research Using Unstructured Electronic Health Record Data to Generate 'Real World' Evidence of Comparative Effectiveness and Safety.

Drug safety Nov 1, 2019
Research that makes secondary use of administrative and clinical healthcare databases is increasingly influential for regulatory, reimbursement, and other healthcare decision-making. Consequently, there are numerous guidance documents on reporting fo...
Research Design Humans Information Storage and Retrieval Electronic Health Records Decision Support Techniques Natural Language Processing Algorithms Databases, Factual
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Real world evidence in cardiovascular medicine: ensuring data validity in electronic health record-based studies.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: With growing availability of digital health data and technology, health-related studies are increasingly augmented or implemented using real world data (RWD). Recent federal initiatives promote the use of RWD to make clinical assertions th...
Information Storage and Retrieval Electronic Health Records Machine Learning Humans Cardiovascular Diseases Cardiology Retrospective Studies Data Mining Natural Language Processing Datasets as Topic Artificial Intelligence
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Putting the "why" in "EHR": capturing and coding clinical cognition.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
Complaints about electronic health records, including information overload, note bloat, and alert fatigue, are frequent topics of discussion. Despite substantial effort by researchers and industry, complaints continue noting serious adverse effects o...
Information Storage and Retrieval Vocabulary, Controlled Clinical Coding User-Computer Interface Cognition Humans Workload Artificial Intelligence Electronic Health Records
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