Michael T. Lash

According to our database, Michael T. Lash authored at least 15 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The third party logistics provider freight management problem: a framework and deep reinforcement learning approach.

Amin Abbasi-Pooya, Michael T. Lash

Ann. Oper. Res., August, 2024

Impact of the COVID-19 pandemic on the stock market and investor online word of mouth.

Xiaorui Zhu, Shaobo Li, Karthik Srinivasan, Michael T. Lash

Decis. Support Syst., January, 2024

HEX: Human-in-the-loop explainability via deep reinforcement learning.

Michael T. Lash

Decis. Support Syst., 2024

2021

Optimal sepsis patient treatment using human-in-the-loop artificial intelligence.

Akash Gupta, Michael T. Lash, Senthil K. Nachimuthu

Expert Syst. Appl., 2021

2020

Personalized Cardiovascular Disease Risk Mitigation via Longitudinal Inverse Classification.

Michael T. Lash, W. Nick Street

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

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

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

J. Heal. Informatics Res., 2019

2018

Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa.

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

Int. J. Data Min. Bioinform., 2018

Prophit: Causal inverse classification for multiple continuously valued treatment policies.

Michael T. Lash, Qihang Lin, W. Nick Street

CoRR, 2018

2017

Generalized Inverse Classification.

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

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

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

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

Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

A Budget-Constrained Inverse Classification Framework for Smooth Classifiers.

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

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa.

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

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016

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

Michael T. Lash, Kang Zhao

J. Manag. Inf. Syst., 2016

Realistic risk-mitigating recommendations via inverse classification.

Michael T. Lash, W. Nick Street

CoRR, 2016

2015

Early Prediction of Movie Success - What, Who, and When.

Michael T. Lash, Sunyang Fu, Shiyao Wang, Kang Zhao

Proceedings of the Social Computing, Behavioral-Cultural Modeling, and Prediction, 2015