UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering - researchr publication related

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Akil Narayan 0001, Zexin Liu, Jake A. Bergquist, Chantel Charlebois, Sumientra Rampersad, Lindsay C. Rupp, Dana H. Brooks, Dan White, Jess D. Tate, Rob S. MacLeod. UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering. Comp. in Bio. and Med., 152:106407, 2023. [doi]

The following publications are possibly variants of this publication:

Using UncertainSCI to Quantify Uncertainty in Cardiac SimulationsLindsay C. Rupp, Zexin Liu, Jake A. Bergquist, Sumientra Rampersad, Dan White, Jess D. Tate, Dana H. Brooks, Akil Narayan, Rob S. MacLeod. cinc 2020: 1-4 [doi]

UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation PipelinesJess D. Tate, Zexin Liu, Jake A. Bergquist, Sumientra Rampersad, Dan White, Chantel Charlebois, Lindsay C. Rupp, Dana H. Brooks, Rob S. MacLeod, Akil Narayan 0001. jossw, 8(90):4249, October 2023. [doi]

Statistical Framework for Uncertainty Quantification in Computational Molecular ModelingMuhibur Rasheed, Nathan Clement, Abhishek Bhowmick 0001, Chandrajit L. Bajaj. tcbb, 16(4):1154-1167, 2019. [doi]

Statistical Framework for Uncertainty Quantification in Computational Molecular ModelingMuhibur Rasheed, Nathan Clement, Abhishek Bhowmick 0001, Chandrajit Bajaj. bcb 2016: 146-155 [doi]

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