AIMC Topic: New York City

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Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2018
OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening...
Humans Algorithms Decision Support Techniques Electronic Health Records Female Infant, Newborn Risk Factors Aged Aged, 80 and over Young Adult Adult Male Middle Aged Risk Assessment Infant Adolescent HIV Infections Cohort Studies Child, Preschool Child Mass Screening Natural Language Processing Automation New York City
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PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2017
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthca...
Humans Machine Learning Algorithms Electronic Health Records Cohort Studies Computational Biology Models, Statistical Bayes Theorem Heart Failure Patient Readmission New York City
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