AIMC Topic:
Data Mining

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An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2019
OBJECTIVE: We aim to evaluate the effectiveness of advanced deep learning models (eg, capsule network [CapNet], adversarial training [ADV]) for single-domain and multidomain relation extraction from electronic health record (EHR) notes.
Humans Electronic Health Records Data Mining Deep Learning Natural Language Processing Drug-Related Side Effects and Adverse Reactions
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A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience.

Neuroinformatics Jul 1, 2019
The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through ...
Deep Learning Data Mining Neurosciences
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Comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2019
Datasets as Topic Drug-Related Side Effects and Adverse Reactions Data Mining Deep Learning Pharmacovigilance Humans Social Media Neural Networks, Computer Natural Language Processing
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Real-World Evidence, Causal Inference, and Machine Learning.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research May 1, 2019
The current focus on real world evidence (RWE) is occurring at a time when at least two major trends are converging. First, is the progress made in observational research design and methods over the past decade. Second, the development of numerous la...
Humans Machine Learning Health Services Research Algorithms Databases, Factual Epidemiology Causality Data Mining
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Big data and machine learning algorithms for health-care delivery.

The Lancet. Oncology May 1, 2019
Analysis of big data by machine learning offers considerable advantages for assimilation and evaluation of large amounts of complex health-care data. However, to effectively use machine learning tools in health care, several limitations must be addre...
Delivery of Health Care, Integrated Medical Oncology Therapy, Computer-Assisted Health Services Research Neural Networks, Computer Machine Learning Neoplasms Diagnosis, Computer-Assisted Big Data Data Mining Humans
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deepBioWSD: effective deep neural word sense disambiguation of biomedical text data.

Journal of the American Medical Informatics Association : JAMIA May 1, 2019
OBJECTIVE: In biomedicine, there is a wealth of information hidden in unstructured narratives such as research articles and clinical reports. To exploit these data properly, a word sense disambiguation (WSD) algorithm prevents downstream difficulties...
Medical Subject Headings Unified Medical Language System Vocabulary, Controlled Deep Learning Natural Language Processing Data Mining Datasets as Topic Systematized Nomenclature of Medicine Biological Ontologies Neural Networks, Computer Algorithms
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A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro.

Toxicological sciences : an official journal of the Society of Toxicology May 1, 2019
The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidim...
Humans Machine Learning Cells, Cultured Kidney Diseases Data Mining Heme Oxygenase-1 Databases, Factual Risk Assessment Systems Biology Sequestosome-1 Protein Toxicology Cell Shape Primary Cell Culture Cell Nucleus Gene Expression Regulation Kidney Tubules, Proximal
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Text-mined fossil biodiversity dynamics using machine learning.

Proceedings. Biological sciences Apr 24, 2019
Documented occurrences of fossil taxa are the empirical foundation for understanding large-scale biodiversity changes and evolutionary dynamics in deep time. The fossil record contains vast amounts of understudied taxa. Yet the compilation of huge vo...
Bryozoa Machine Learning Biological Evolution Paleontology Animals Fossils Biodiversity Data Mining
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Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2019
OBJECTIVE: Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information doc...
Data Mining Symptom Assessment Databases, Bibliographic Electronic Health Records Humans Narration Algorithms Natural Language Processing
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Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Journal of the American Heart Association Mar 5, 2019
Background The ability to accurately predict the occurrence of in-hospital death after percutaneous coronary intervention is important for clinical decision-making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System...
Male Data Mining New York Stroke Volume Female Hospital Mortality Registries Middle Aged Risk Factors Treatment Outcome Humans Percutaneous Coronary Intervention Aged Age Factors Machine Learning Coronary Artery Disease Databases, Factual
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