Mark P. Sendak

According to our database, Mark P. Sendak authored at least 15 papers between 2016 and 2023.

Collaborative distances:

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

2023

A framework for understanding label leakage in machine learning for health care.

Sharon E. Davis, Michael E. Matheny, Suresh Balu, Mark P. Sendak

J. Am. Medical Informatics Assoc., December, 2023

Enabling collaborative governance of medical AI.

W. Nicholson Price, Mark P. Sendak, Suresh Balu, Karandeep Singh

Nat. Mac. Intell., August, 2023

Accelerating health system innovation: principles and practices from the Duke Institute for Health Innovation.

Sahil Sandhu, Mark P. Sendak, William Ratliff, William Knechtle, William J. Fulkerson, Suresh Balu

Patterns, April, 2023

Editorial: Surfacing best practices for AI software development and integration in healthcare.

Mark P. Sendak, David Vidal, Sylvia Trujillo, Karandeep Singh, Xiaoxuan Liu, Suresh Balu

Frontiers Digit. Health, March, 2023

Organizational Governance of Emerging Technologies: AI Adoption in Healthcare.

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 Vidal, Suresh Balu, Mark P. Sendak

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Development and Validation of ML-DQA - a Machine Learning Data Quality Assurance Framework for Healthcare.

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

Proceedings of the Machine Learning for Healthcare Conference, 2022

2021

Looking for clinician involvement under the wrong lamp post: The need for collaboration measures.

Mark P. Sendak, Michael Gao, William Ratliff, Marshall Nichols, Armando Bedoya, Cara O'Brien, Suresh Balu

J. Am. Medical Informatics Assoc., 2021

Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study.

Aman Kansal, Michael Gao, Suresh Balu, Marshall Nichols, Kristin Corey, Sehj Kashyap, Mark P. Sendak

Int. J. Medical Informatics, 2021

2020

Presenting machine learning model information to clinical end users with model facts labels.

Mark P. Sendak, Michael Gao, Nathan Brajer, Suresh Balu

npj Digit. Medicine, 2020

"The human body is a black box": supporting clinical decision-making with deep learning.

Mark P. Sendak, Madeleine Clare Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, Cara O'Brien

Proceedings of the FAT* '20: Conference on Fairness, 2020

2019

Translating, Implementing, Deploying, and Evaluating Clinical Interventions Using Machine Learning Based Predictive Models: Illustrative Case Studies.

Yindalon Aphinyanaphongs, Jonathan K. Wilt, Corey J. Chivers, Mark P. Sendak

Proceedings of the AMIA 2019, 2019

2017

Barriers to Achieving Economies of Scale in Analysis of EHR Data.

Mark P. Sendak, Suresh Balu, Kevin A. Schulman

Appl. Clin. Inform., 2017

An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection.

Joseph Futoma, Sanjay Hariharan, Katherine A. Heller, Mark P. Sendak, Nathan Brajer, Meredith Clement, Armando Bedoya, Cara O'Brien

Proceedings of the Machine Learning for Health Care Conference, 2017

2016

Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease.

Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data.

Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller

Proceedings of the 1st Machine Learning in Health Care, 2016