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Volumn 54, Issue 6, 2015, Pages 546-547

Big data and analytics in healthcare

Author keywords

Big data; Healthcare analytics; Healthcare informatics; Natural language processing; Predictive analytics

Indexed keywords

CLASSIFICATION; DATA MINING; ELECTRONIC HEALTH RECORD; INFORMATION PROCESSING; MEANINGFUL USE CRITERIA; MEDICAL RECORD; ORGANIZATION AND MANAGEMENT; PROCEDURES; STATISTICS AND NUMERICAL DATA;

EID: 84948185748     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.3414/ME15-06-1001     Document Type: Editorial
Times cited : (45)

References (10)
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    • Baro, E.1    Degoul, S.2    Beuscart, R.3    Chazard, E.4
  • 5
    • 85009503457 scopus 로고    scopus 로고
    • April 21, (accessed Oct 27, 2015)
    • Marr B. How Big Data Is Changing Health- care. April 21, 2015. http://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is- changing-healthcare/print/ (accessed Oct 27, 2015)
    • (2015) How Big Data is Changing Health- Care
    • Marr, B.1
  • 6
    • 84948157699 scopus 로고    scopus 로고
    • Elsevier Con- nect. October 6, (accessed October 27, 2015)
    • Winters-Miner LA. Seven ways predictive analytics can improve healthcare. Elsevier Con- nect. October 6, 2014. https://www.elsevier.com/connect/seven-ways-predictive-analytics-can-improve-healthcare (accessed October 27, 2015)
    • (2014) Seven Ways Predictive Analytics Can Improve Healthcare
    • Winters-Miner, L.A.1
  • 7
    • 80051736192 scopus 로고    scopus 로고
    • Predictive analytics in information systems research
    • Shmueli G, Koppius OR. Predictive analytics in information systems research. MIS Quarterly 2011; 35 (3): 553–572
    • (2011) MIS Quarterly , vol.35 , Issue.3 , pp. 553-572
    • Shmueli, G.1    Koppius, O.R.2
  • 8
    • 84948160628 scopus 로고    scopus 로고
    • Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes
    • Divita G, Carter M, Redd A, Zeng Q, Gupta K, Trautner B et al. Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes. Methods Inf Med 2015; 54 (6): 548–552
    • (2015) Methods Inf Med , vol.54 , Issue.6 , pp. 548-552
    • Divita, G.1    Carter, M.2    Redd, A.3    Zeng, Q.4    Gupta, K.5    Trautner, B.6
  • 9
    • 84948176991 scopus 로고    scopus 로고
    • A Generalized Multilevel Regression Model Using Longitudinal Data to Predict Depression among Patients with Diabetes
    • Jin H, Wu S, Vidyanti I, Di Capua P, Wu B. A Generalized Multilevel Regression Model Using Longitudinal Data to Predict Depression among Patients with Diabetes. Methods Inf Med 2015; 54 (6): 553–559
    • (2015) Methods Inf Med , vol.54 , Issue.6 , pp. 553-559
    • Jin, H.1    Wu, S.2    Vidyanti, I.3    Di Capua, P.4    Wu, B.5
  • 10
    • 84948145265 scopus 로고    scopus 로고
    • Predicting 30-Day Hospital Readmission with Pub lically Available Administrative Database: A Conditional Logistic Regression Approach
    • Zhu K, Lou Z, Ballester N, Kong N, Parikh PJ. Predicting 30-Day Hospital Readmission with Pub lically Available Administrative Database: A Conditional Logistic Regression Approach. Methods Inf Med 2015; 54 (6): 560–567
    • (2015) Methods Inf Med , vol.54 , Issue.6 , pp. 560-567
    • Zhu, K.1    Lou, Z.2    Ballester, N.3    Kong, N.4    Parikh, P.J.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.