A new, accurate predictive model for incident hypertension

Journal of Hypertension

Volumn 31, Issue 11, 2013, Pages 2142-2150

  Völzke, Henry ^a   Fung, Glenn ^b   Ittermann, Till ^a   Yu, Shipeng ^b   Baumeister, Sebastian E ^a   Dörr, Marcus ^a   Lieb, Wolfgang ^c   Völker, Uwe ^a   Linneberg, Allan ^d   Jørgensen, Torben ^d,e   Felix, Stephan B ^a   Rettig, Rainer ^a   Rao, Bharat ^b   Kroemer, Heyo K ^f  

^a UNIVERSITY OF GREIFSWALD   (Germany)

^b SIEMENS CORPORATE RESEARCH   (United States)

^c UNIVERSITY OF KIEL   (Germany)

^d GLOSTRUP UNIVERSITY HOSPITAL   (Denmark)

^e UNIVERSITY OF COPENHAGEN   (Denmark)

^f UNIVERSITY MEDICAL CENTER GÖTTINGEN   (Germany)

Author keywords

data mining; epidemiology; hypertension; prediction

Indexed keywords

ADULT; AGE; AGED; ALGORITHM; BAYES THEOREM; DATA MINING; FEMALE; GERMANY; HUMAN; HYPERTENSION; MALE; MIDDLE AGED; RANDOMIZATION; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; RISK FACTOR; THEORETICAL MODEL; YOUNG ADULT;

ADULT; AGE FACTORS; AGED; ALGORITHMS; BAYES THEOREM; DATA MINING; FEMALE; GERMANY; HUMANS; HYPERTENSION; MALE; MIDDLE AGED; MODELS, THEORETICAL; RANDOM ALLOCATION; RISK ASSESSMENT; RISK FACTORS; ROC CURVE; YOUNG ADULT;

EID: 84885584388     PISSN: 02636352     EISSN: 14735598     Source Type: Journal    
DOI: 10.1097/HJH.0b013e328364a16d     Document Type: Article

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