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Use of machine learning to determine stroke severity of patients diagnosed with stroke in claims data

25 August 2018 (00:00 - 00:00)
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Congress Presentation Part of: Atrial fibrillation, stroke and cardiovascular risk Big Data Analysis ESC Premium Access ESC Congress 2018

About the speaker

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Doctor Emily Kogan

Janssen Pharmaceutical Companies of Johnson and Johnson, Raritan (United States of America)

6 More presentations in this session

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Comparison of analysis methodologies for net outcome with edoxaban vs warfarin in patients with atrial fibrillation in the ENGAGE AF-TIMI 48 trial
Mrs R. Hamershock (Boston, US)
Abstract Slides
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Safety and effectiveness of dabigatran relative to warfarin in routine care: final results from a long-term monitoring program
Doctor K. Zint (Ingelheim, DE)
Abstract
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National prescribing and adverse event rates of patients at risk of stroke with non-valvular AF from CPRD linked database: does 'big data' reflect clinical trials and identify areas for improvement?
Doctor V. Mehta (London, GB)
Abstract Slides
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Comparison of long DAPT versus short DAPT in Japanese PCI patients based on healthcare information database
Doctor H. Yokoi (Fukuoka, JP)
Abstract Slides
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Assessment of cardiovascular disease risk using different thresholds to define high risk on the pooled cohort equations
Doctor R. Rosenson (New York City, US)
Abstract Slides

Access the full session

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Atrial fibrillation, stroke and cardiovascular risk

The Event

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ESC Congress 2018

25 August - 29 August 2018

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources