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ORIGINAL ARTICLES

A Monte Carlo approach to the estimation & analysis of uncertainty in clinical laboratory measurement processes

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Pages 1-13 | Received 01 Nov 2010, Accepted 01 Feb 2012, Published online: 09 May 2012

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Varun Ramamohan, James T. Abbott, George G. Klee & Yuehwern Yih. (2015) Modeling the effect of instrument drift in clinical laboratories: A serum bilirubin assay case study. IIE Transactions on Healthcare Systems Engineering 5:3, pages 147-164.
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Matteo Vidali. (2023) Use of Computer Simulation for Calculating Reference Limits for Distribution Overlap. The Journal of Applied Laboratory Medicine 8:1, pages 106-112.
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Hui Yang & Eva K. LeeVarun Ramamohan, James T. Abbott & Yuehwern Yih. 2016. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement 127 157 .
Varun Ramamohan, James T. Abbott & Yuehwern Yih. (2015) A mathematical model of measurement uncertainty of single substrate enzyme assays. Journal of Chemometrics 29:1, pages 49-58.
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Varun Ramamohan, James T. Abbott & Yuehwern Yih. (2014) A simulation-based approach to modeling the uncertainty of two-substrate clinical enzyme measurement processes. A simulation-based approach to modeling the uncertainty of two-substrate clinical enzyme measurement processes.
Varun Ramamohan, James T. Abbott, George G. Klee & Yuehwern Yih. (2014) Modeling, analysis and optimization of calibration uncertainty in clinical laboratories. Measurement 50, pages 175-185.
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Varun Ramamohan, Yuehwern Yih, James T. Abbott & George G. Klee. (2013) Category-specific uncertainty modeling in clinical laboratory measurement processes. Clinical Chemistry and Laboratory Medicine (CCLM) 51:12, pages 2273-2280.
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