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Volumn 320, Issue 1, 2018, Pages 27-28

Big data and predictive analytics: Recalibrating expectations

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL DECISION MAKING; ELECTRONIC HEALTH RECORD; HEALTH CARE COST; HEALTH CARE DELIVERY; HEALTH CARE QUALITY; HEALTH CARE SYSTEM; NOTE; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; DECISION SUPPORT SYSTEM; HUMAN; INFORMATION PROCESSING; MACHINE LEARNING; PROCEDURES; RISK ASSESSMENT;

EID: 85049715780     PISSN: 00987484     EISSN: 15383598     Source Type: Journal    
DOI: 10.1001/jama.2018.5602     Document Type: Note
Times cited : (206)

References (7)
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  • 2
    • 85055267920 scopus 로고    scopus 로고
    • Tufts PACE Clinical Prediction Model Registry: Update 1990 through 2015
    • Wessler BS, Paulus JK, Lundquist C, et al. Tufts PACE Clinical Prediction Model Registry: update 1990 through 2015. Diagn Progn Res. 2017;1 (20):1-8. doi:10.1186/s41512-017-0021-2
    • (2017) Diagn Progn Res , vol.1 , Issue.20 , pp. 1-8
    • Wessler, B.S.1    Paulus, J.K.2    Lundquist, C.3
  • 3
    • 33750905259 scopus 로고    scopus 로고
    • Decision curve analysis: A novel method for evaluating prediction models
    • Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565-574. doi:10.1177/0272989X06295361
    • (2006) Med Decis Making , vol.26 , Issue.6 , pp. 565-574
    • Vickers, A.J.1    Elkin, E.B.2
  • 4
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    • Assessing the performance of prediction models: A framework for traditional and novel measures
    • Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21(1):128-138. doi:10.1097/EDE .0b013e3181c30fb2
    • (2010) Epidemiology , vol.21 , Issue.1 , pp. 128-138
    • Steyerberg, E.W.1    Vickers, A.J.2    Cook, N.R.3
  • 5
    • 84921383600 scopus 로고    scopus 로고
    • Calibration of risk prediction models: Impact on decision-analytic performance
    • Van Calster B, Vickers AJ. Calibration of risk prediction models: impact on decision-analytic performance. Med Decis Making. 2015;35(2):162-169. doi:10.1177/0272989X14547233
    • (2015) Med Decis Making , vol.35 , Issue.2 , pp. 162-169
    • Van Calster, B.1    Vickers, A.J.2
  • 6
    • 77958090625 scopus 로고    scopus 로고
    • External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients
    • Vergouwe Y, Moons KG, Steyerberg EW. External validity of risk models: use of benchmark values to disentangle a case-mix effect from incorrect coefficients. Am J Epidemiol. 2010;172(8):971-980. doi:10.1093/aje/kwq223
    • (2010) Am J Epidemiol , vol.172 , Issue.8 , pp. 971-980
    • Vergouwe, Y.1    Moons, K.G.2    Steyerberg, E.W.3
  • 7
    • 85007529863 scopus 로고    scopus 로고
    • Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
    • Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016;316(22):2402-2410. doi:10.1001/jama.2016.17216
    • (2016) JAMA , vol.316 , Issue.22 , pp. 2402-2410
    • Gulshan, V.1    Peng, L.2    Coram, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.