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Published in IADC/SPE International Drilling Conference and Exhibition 2020, 2020
This explores the performance of basic NLP classifiers that classify daily driller memos into a wide variety of activity codes.
Recommended citation: Ucherek, Jared & Lawal, Tesleem & Prinz, Matthew & Li, Lisa & Ashok, Pradeepkumar & van Oort, Eric & Gobert, Tatiana & Mejia, Juan. (2020). Auto-Suggestive Real-Time Classification of Driller Memos into Activity Codes for Invisible Lost Time Analysis. 10.2118/199593-MS.
Published in Machine Learning for Healthcare, 2020
We develop vanilla machine learning models competitive with contemporary black-box models used in sepsis prediction. Our work illustrates the importance of rigorously defining the difficulty of your targeted task when developing novel solutions.
Recommended citation: Snyder, Christopher; Ucherek, Jared; Vishwanath, Sriram. (2020). The Importance of Baseline Models in Sepsis Prediction.