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Mark P. Sendak
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- affiliation: Duke Institute for Health Innovation, Durham, NC, USA
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2020 – today
- 2024
- [j11]Mark P. Sendak
, Vincent X. Liu, Ashley Beecy
Strengthening the use of artificial intelligence within healthcare delivery organizations: balancing regulatory compliance and patient safety. J. Am. Medical Informatics Assoc. 31(7): 1622-1627 (2024) - [j10]Michelle Pistner Nixon, Farhani Momotaz, Claire Smith, Jeffrey S. Smith, Mark P. Sendak
From pre-test and post-test probabilities to medical decision making. BMC Medical Informatics Decis. Mak. 24(1): 210 (2024) - [j9]William Boag, Alifia Hasan
The algorithm journey map: a tangible approach to implementing AI solutions in healthcare. npj Digit. Medicine 7(1) (2024) - 2023
- [j8]Mark P. Sendak
Editorial: Surfacing best practices for AI software development and integration in healthcare. Frontiers Digit. Health 5 (2023) - [j7]Sharon E. Davis
A framework for understanding label leakage in machine learning for health care. J. Am. Medical Informatics Assoc. 31(1): 274-280 (2023) - [j6]W. Nicholson Price
Enabling collaborative governance of medical AI. Nat. Mac. Intell. 5(8): 821-823 (2023) - [j5]Sahil Sandhu
Accelerating health system innovation: principles and practices from the Duke Institute for Health Innovation. Patterns 4(4): 100710 (2023) - [c7]Jee Young Kim
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. FAccT 2023: 1396-1417 - [i3]Jee Young Kim, William Boag, Freya Gulamali, Alifia Hasan, Henry David Jeffry Hogg, Mark Lifson, Deirdre K. Mulligan, Manesh Patel, Inioluwa Deborah Raji, Ajai Sehgal, Keo Shaw, Danny Tobey, Alexandra Valladares, David E. Vidal, Suresh Balu, Mark P. Sendak:
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. CoRR abs/2304.13081 (2023) - 2022
- [c6]Mark P. Sendak, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo, Linda Tang, Kira Niederhoffer, Sarah Reed, Kaivalya Deshpande, Emily Sterrett, Melissa Bauer, Laurie Snyder, Afreen Shariff, David Whellan, Jeffrey Riggio, David Gaieski, Kristin Corey, Megan Richards, Michael Gao, Marshall Nichols, Bradley Heintze, William Knechtle, William Ratliff, Suresh Balu:
Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. MLHC 2022: 741-759 - [e2]Zachary C. Lipton, Rajesh Ranganath, Mark P. Sendak, Michael W. Sjoding, Serena Yeung:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2022, 5-6 August 2022, Durham, NC, USA. Proceedings of Machine Learning Research 182, PMLR 2022 [contents] - [i2]Mark P. Sendak
Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare. CoRR abs/2208.02670 (2022) - 2021
- [j4]Aman Kansal
Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study. Int. J. Medical Informatics 151: 104466 (2021) - [j3]Mark P. Sendak
Looking for clinician involvement under the wrong lamp post: The need for collaboration measures. J. Am. Medical Informatics Assoc. 28(11): 2541-2542 (2021) - [e1]Ken Jung, Serena Yeung, Mark P. Sendak, Michael W. Sjoding, Rajesh Ranganath:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2021, 6-7 August 2021, Virtual Event. Proceedings of Machine Learning Research 149, PMLR 2021 [contents] - 2020
- [j2]Mark P. Sendak
Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Medicine 3 (2020) - [c5]Mark P. Sendak
"The human body is a black box": supporting clinical decision-making with deep learning. FAT* 2020: 99-109
2010 – 2019
- 2019
- [c4]Yindalon Aphinyanaphongs, Jonathan K. Wilt, Corey J. Chivers, Mark P. Sendak:
Translating, Implementing, Deploying, and Evaluating Clinical Interventions Using Machine Learning Based Predictive Models: Illustrative Case Studies. AMIA 2019 - [i1]Mark P. Sendak, Madeleine Clare Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, Cara O'Brien:
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning. CoRR abs/1911.08089 (2019) - 2017
- [j1]Mark P. Sendak
Barriers to Achieving Economies of Scale in Analysis of EHR Data. Appl. Clin. Inform. 08(03): 826-831 (2017) - [c3]Joseph Futoma, Sanjay Hariharan, Katherine A. Heller, Mark P. Sendak, Nathan Brajer, Meredith Clement, Armando Bedoya, Cara O'Brien:
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection. MLHC 2017: 243-254 - 2016
- [c2]Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller:
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data. MLHC 2016: 42-54 - [c1]Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller:
Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. UAI 2016
Coauthor Index
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last updated on 2024-11-15 19:33 CET by the dblp team
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