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OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI
Sweeney, Elizabeth M., Shinohara, Russell T., Shiee, Navid, Mateen, Farrah J., Chudgar, Avni A., Cuzzocreo, Jennifer L., Calabresi, Peter A., Pham, Dzung L., Reich, Daniel S., Crainiceanu, Ciprian M.
Published in NeuroImage clinical (01.01.2013)
Published in NeuroImage clinical (01.01.2013)
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Optimal Statistical Inference in the Presence of Systematic Uncertainties Using Neural Network Optimization Based on Binned Poisson Likelihoods with Nuisance Parameters
Wunsch, Stefan, Jörger, Simon, Wolf, Roger, Quast, Günter
Published in Computing and software for big science (01.12.2021)
Published in Computing and software for big science (01.12.2021)
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Statistical inference on restricted partial linear regression models with partial distortion measurement errors
Zhang, Jun, Zhou, Nanguang, Sun, Zipeng, Li, Gaorong, Wei, Zhenghong
Published in Statistica Neerlandica (01.11.2016)
Published in Statistica Neerlandica (01.11.2016)
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Stable between-subject statistical inference from unstable within-subject functional connectivity estimates
Vidaurre, Diego, Woolrich, Mark W., Winkler, Anderson M., Karapanagiotidis, Theodoros, Smallwood, Jonathan, Nichols, Thomas E.
Published in Human Brain Mapping (19.02.2018)
Published in Human Brain Mapping (19.02.2018)
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Statistical inference for heteroscedastic semi-varying coefficient EV models
Zhao, Fanrong, Song, Weixing, Shi, Jianhong
Published in Communications in statistics. Theory and methods (19.05.2018)
Published in Communications in statistics. Theory and methods (19.05.2018)
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