David Scheinker

According to our database, David Scheinker authored at least 15 papers between 2016 and 2022.

Collaborative distances:

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

2022

The Design and Implementation of a Broadly Applicable Algorithm for Optimizing Intra-Day Surgical Scheduling.

Jin Xie, Teng Zhang, Jose H. Blanchet, Peter W. Glynn, Matthew Randolph, David Scheinker

CoRR, 2022

Surgical Scheduling via Optimization and Machine Learning with Long-Tailed Data.

Yuan Shi, Saied Mahdian, Jose H. Blanchet, Peter W. Glynn, Andrew Young Shin, David Scheinker

CoRR, 2022

Visualizing Opioid-Use Variation in a Pediatric Perioperative Dashboard.

Conrad W. Safranek, Lauren E. Feitzinger, Alice Kate Cummings Joyner, Nicole Woo, Virgil Smith, Elizabeth De Souza, Christos Vasilakis, Thomas Anthony Anderson, James Fehr, Andrew Young Shin, David Scheinker, Ellen Wang, James Xie

Appl. Clin. Inform., 2022

2021

A personalized decision aid for prostate cancer shared decision making.

Hilary P. Bagshaw, Alejandro Martinez, Nastaran Heidari, David Scheinker, Alan Pollack, Radka Stoyanova, Eric Horwitz, Gerard Morton, Amar U. Kishan, Mark Buyyounouski

BMC Medical Informatics Decis. Mak., 2021

The design and evaluation of a novel algorithm for automated preference card optimization.

David Scheinker, Matt Hollingsworth, Anna Brody, Carey Phelps, William Bryant, Francesca Pei, Kristin Petersen, Alekhya Reddy, James Wall

J. Am. Medical Informatics Assoc., 2021

2020

Machine learning and atherosclerotic cardiovascular disease risk prediction in a multi-ethnic population.

Andrew Ward, Ashish Sarraju, Sukyung Chung, Jiang Li, Robert A. Harrington, Paul Heidenreich, Latha Palaniappan, David Scheinker, Fátima Rodriguez

npj Digit. Medicine, 2020

Implementing Analytics Projects in a Hospital: Successes, Failures, and Opportunities.

David Scheinker, Margaret L. Brandeau

INFORMS J. Appl. Anal., 2020

Extremum Seeking for Creating Optimal Feedback Controls of Unknown Systems by Tuning Basis Functions.

Alexander Scheinker, David Scheinker

Proceedings of the 2020 American Control Conference, 2020

2019

Anesthesiologist Surgery Assignments using Policy Learning.

Andrew Ward, Zhengyuan Zhou, Nicholas Bambos, Ellen Wang, David Scheinker

Proceedings of the 2019 IEEE International Conference on Communications, 2019

Noninvasive Identification of Hypotension Using Convolutional-Deconvolutional Networks.

Daniel Miller, Andrew Ward, Nicholas Bambos, Andrew Young Shin, David Scheinker

Proceedings of the 2019 IEEE International Conference on E-health Networking, 2019

2018

Physiological Waveform Imputation of Missing Data using Convolutional Autoencoders.

Daniel Miller, Andrew Ward, Nicholas Bambos, David Scheinker, Andrew Young Shin

Proceedings of the 20th IEEE International Conference on e-Health Networking, 2018

2017

Improving predictions of pediatric surgical durations with supervised learning.

Neal Master, Zhengyuan Zhou, Daniel Miller, David Scheinker, Nicholas Bambos, Peter W. Glynn

Int. J. Data Sci. Anal., 2017

2016

Extremum Seeking for Stabilization of Systems Not Affine in Control.

Alexander Scheinker, David Scheinker

CoRR, 2016

Bounded extremum seeking with discontinuous dithers.

Alexander Scheinker, David Scheinker

Autom., 2016

Detecting Inaccurate Predictions of Pediatric Surgical Durations.

Zhengyuan Zhou, Daniel Miller, Neal Master, David Scheinker, Nicholas Bambos, Peter W. Glynn

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016