AIMC Topic: Washington

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The machine giveth and the machine taketh away: a parrot attack on clinical text deidentified with hiding in plain sight.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: Clinical corpora can be deidentified using a combination of machine-learned automated taggers and hiding in plain sight (HIPS) resynthesis. The latter replaces detected personally identifiable information (PII) with random surrogates, allo...
Humans Machine Learning Delivery of Health Care Electronic Health Records Confidentiality Data Anonymization Ambulatory Care Facilities Computer Security Washington Personally Identifiable Information
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Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

Accident; analysis and prevention Mar 1, 2018
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual int...
Humans Machine Learning Environment Design Models, Statistical Pedestrians Accidents, Traffic Spatial Analysis Multivariate Analysis Washington
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