Seattle Children's Hospital

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Scott Lundberg, Bala G. Nair, Monica S. Vavilala et al.

2018 · 1.911 Zit.

Crowd-Sourced Assessment of Technical Skills: a novel method to evaluate surgical performance

Carolyn Chen, Lee White, Timothy M. Kowalewski et al.

2013 · 164 Zit.

Use of Artificial Intelligence in Radiology: Impact on Pediatric Patients, a White Paper From the ACR Pediatric AI Workgroup

Marla B. K. Sammer, Yasmin S. Akbari, Richard A. Barth et al.

2023 · 59 Zit.

Machine learning concepts, concerns and opportunities for a pediatric radiologist

Michael M. Moore, Einat Slonimsky, Aaron Long et al.

2019 · 58 Zit.

Bias and ethical considerations in machine learning and the automation of perioperative risk assessment

Vikas N. O’Reilly-Shah, Katherine R. Gentry, Andrew M. Walters et al.

2020 · 57 Zit.

Equity and the JAMA Network

Phil Fontanarosa, Annette Flanagin, John Z. Ayanian et al.

2021 · 39 Zit.

Explainable machine learning predictions to help anesthesiologists prevent hypoxemia during surgery

Scott Lundberg, Bala G. Nair, Monica S. Vavilala et al.

2017 · 35 Zit.

The current and future roles of artificial intelligence in pediatric radiology

Jeffrey P. Otjen, Michael M. Moore, Erin K. Romberg et al.

2021 · 33 Zit.

An international study presenting a federated learning AI platform for pediatric brain tumors

Edward H. Lee, Michelle Han, Jason L. Wright et al.

2024 · 32 Zit.

Artificial Intelligence for Language Translation

K. Casey Lion, Yu-Hsiang Lin, Theresa Y. Kim

2024 · 27 Zit.

Do ChatGPT and Gemini Provide Appropriate Recommendations for Pediatric Orthopaedic Conditions?

Sean Pirkle, JaeWon Yang, Todd J. Blumberg

2024 · 27 Zit.

An ethics framework for consolidating and prioritizing COVID-19 clinical trials

Michelle N. Meyer, Luke Gelinas, Barbara E. Bierer et al.

2021 · 23 Zit.

Big Data and Ethics Review for Health Systems Research in LMICs: Understanding Risk, Uncertainty and Ignorance—And Catching the Black Swans?

Türkay Dereli, Yavuz Çoşkun, Eugene Kolker et al.

2014 · 23 Zit.

Machine Learning and Statistics in Clinical Research Articles—Moving Past the False Dichotomy

Samuel G. Finlayson, Andrew L. Beam, Maarten van Smeden

2023 · 22 Zit.

CANAIRI: the Collaboration for Translational Artificial Intelligence Trials in healthcare

Melissa D. McCradden, Alex John London, Judy Wawira Gichoya et al.

2025 · 18 Zit.