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Personalized Cardiovascular Disease Risk Mitigation via Longitudinal Inverse Classification


Nov 16, 2020
Michael T. Lash, W. Nick Street

* Forthcoming in AIBH 2020 (a BIBM 2020 workshop) 

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Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence


Sep 16, 2020
Akash Gupta, Michael T. Lash, Senthil K. Nachimuthu


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Deriving Enhanced Geographical Representations via Similarity-based Spectral Analysis: Predicting Colorectal Cancer Survival Curves in Iowa


Sep 06, 2018
Michael T. Lash, Min Zhang, Xun Zhou, W. Nick Street, Charles F. Lynch

* arXiv admin note: substantial text overlap with arXiv:1708.04714 

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Prophit: Causal inverse classification for multiple continuously valued treatment policies


Feb 14, 2018
Michael T. Lash, Qihang Lin, W. Nick Street


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21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models


Jan 26, 2018
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre

* arXiv admin note: substantial text overlap with arXiv:1705.03540 

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Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa


Aug 15, 2017
Michael T. Lash, Yuqi Sun, Xun Zhou, Charles F. Lynch, W. Nick Street

* 8 pages 

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A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models


Jul 07, 2017
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre

* Accepted to ICHI 2017. 8 pages 

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A budget-constrained inverse classification framework for smooth classifiers


Jun 08, 2017
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson


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Generalized Inverse Classification


Jan 12, 2017
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson, Jeffrey Ohlmann

* Accepted to SDM 2017. Full paper + supplemental material 

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Realistic risk-mitigating recommendations via inverse classification


Nov 13, 2016
Michael T. Lash, W. Nick Street


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Early Predictions of Movie Success: the Who, What, and When of Profitability


Jan 29, 2016
Michael T. Lash, Kang Zhao


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