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Volumn , Issue , 2017, Pages 241-244

Visualization of patient specific disease risk prediction

Author keywords

[No Author keywords available]

Indexed keywords

ABSTRACT DATA TYPES; ARTIFICIAL INTELLIGENCE; DATA MINING; DIAGNOSIS; HEALTH CARE; LEARNING SYSTEMS; MEDICAL COMPUTING; MULTIMEDIA SYSTEMS; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION;

EID: 85018380124     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BHI.2017.7897250     Document Type: Conference Paper
Times cited : (8)

References (18)
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  • 6
    • 0029095994 scopus 로고
    • Estimation of mean sojourn time in breast cancer screening using a Markov chain model of both entry to and exit from the preclinical detectable phase
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  • 8
    • 80955124079 scopus 로고    scopus 로고
    • Use of electronic medical records (EMR) for oncology outcomes research: Assessing the comparability of EMR information to patient registry and health claims data
    • E. C. Lau et al. Use of electronic medical records (EMR) for oncology outcomes research: assessing the comparability of EMR information to patient registry and health claims data. Clinical Epidemiology, 2011
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    • Lau, E.C.1
  • 9
    • 84877621597 scopus 로고    scopus 로고
    • Health providers' perceptions of novel approaches to visualizing integrated health information
    • T. Le et al. Health providers' perceptions of novel approaches to visualizing integrated health information. Methods of Information in Medicine, 2013
    • (2013) Methods of Information in Medicine
    • Le, T.1
  • 12
    • 84958661312 scopus 로고    scopus 로고
    • Visualization: A mind-machine interface for discovery
    • C. B. Nielsen. Visualization a mind-machine interface for discovery. Trends in Genetics, 2016
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    • Nielsen, C.B.1
  • 13
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    • Thuemmler, C.1
  • 18
    • 84968543936 scopus 로고    scopus 로고
    • Defining disease phenotypes in primary care electronic health records by a machine learning approach: A case study in identifying rheumatoid arthritis
    • S.-M. Zhou et al. Defining disease phenotypes in primary care electronic health records by a machine learning approach a case study in identifying rheumatoid arthritis. PLOS ONE, 2016
    • (2016) PLOS ONE
    • Zhou, S.-M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.