med watch dashboard - big data mining on safety information and adverse event reports

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MED Watch Dashboard Big Data Mining on Safety Information and Adverse Event Reports http://medwatch.co.nf Budapest Users of R Network, 2014.01.15

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Page 1: MED Watch Dashboard - Big Data Mining on Safety Information and Adverse Event Reports
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Data Source (FDA)

•  2012 Q4 Safety Alerts for Human Medical Products (Drugs, Biologics, Medical Devices, Special Nutritionals, and Cosmetics)

•  The alerts contain actionable information that may impact both treatment and diagnostic choices for healthcare professional and patient.

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MED Watch Dashboard Viewers http://medwatch.co.nf

December of 2013

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Data Clean - 1

•  The raw reported data have been cleaned according to the International Conference on Harmonisation (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use.

•  The verbatim reactions/indications have been coded into the system organ class (SOC) using the Medical Dictionary for Regulatory Activities (MedDRA version 13.1) for coding of diseases/medical conditions.

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Data Clean - 2

●  The raw reported datasets have been transferred into CDISC SDTM datasets, and also into CDISC ADaM datasets which are the basis for production of statistical graphs in R statistical package including: –  Shiny, –  vcd (The conditional density plot - Hofmann and Theus

2005), –  Basic Hexagon Binning Functions (hexbin) –  rworldmap(joinCountryData2Map, mapCountryData), –  ggplot2.

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LIE Factor - Edward Tufte Define the maximum ideas to the audience:

•  In the shortest time,

•  Minimize the number of "ink", with the smallest optimal representation.

•  Tell the truth about the data.

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