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Using statistical text classification to identify health information technology incidents.

Using statistical text classification to identify health information technology incidents.

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Big data in medicine is driving big changes Using multiclass classification to automate the identification of patient safety incident reports by type and severity.Automatic detection of tweets reporting cases of influenza like illnesses in Australia Reporting medical device safety incidents to regulatory authorities: An analysis and classification of technology-induced errors.Using Active Learning to Identify Health Information Technology Related Patient Safety Events.An analysis of electronic health record-related patient safety incidents.Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.Statistical classification of drug incidents due to look-alike sound-alike mix-ups.A Primer to the Structure, Content and Linkage of the FDA's Manufacturer and User Facility Device Experience (MAUDE) Files.

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Using statistical text classification to identify health information technology incidents.

http://www.wikidata.org/entity/Q37129501

description

article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 10 May 2013

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vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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Using statistical text classif ...... ormation technology incidents.

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Using statistical text classif ...... ormation technology incidents.

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Using statistical text classif ...... ormation technology incidents.

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Using statistical text classif ...... ormation technology incidents.

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Using statistical text classif ...... ormation technology incidents.

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Using statistical text classif ...... ormation technology incidents.

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AMIAJNL-2012-001409

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Journal of the American Medical Informatics Association

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Using statistical text classification to identify health information technology incidents

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Farah Magrabi

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Stephen Anthony

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Challenges in ethics, safety, best practices, and oversight regarding HIT vendors, their customers, and patients: a report of an AMIA special task force

An analysis of computer-related patient safety incidents to inform the development of a classification.

Health information technology: fallacies and sober realities.

Anticipating and addressing the unintended consequences of health IT and policy: a report from the AMIA 2009 Health Policy Meeting

The effect of electronic prescribing on medication errors and adverse drug events: a systematic review.

Setting priorities for patient safety.

Using FDA reports to inform a classification for health information technology safety problems.

The dangerous decade

Automated discovery of drug treatment patterns for endocrine therapy of breast cancer within an electronic medical record

Automated identification of extreme-risk events in clinical incident reports.

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scholarly article

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10.1136/AMIAJNL-2012-001409

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Enrico W. Coiera

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2013-05-10T00:00:00Z

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