Melissa D. McCradden

According to our database, Melissa D. McCradden authored at least 12 papers between 2019 and 2023.

Collaborative distances:

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

2023

A normative framework for artificial intelligence as a sociotechnical system in healthcare.

Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London

Patterns, November, 2023

The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols.

Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins

Nat. Mac. Intell., August, 2023

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging.

Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker

CoRR, 2023

What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB.

Melissa D. McCradden, Oluwadara Odusi, Shalmali Joshi, Ismail Akrout, Kagiso Ndlovu, Ben Glocker, Gabriel Maicas, Xiaoxuan Liu, Mjaye Mazwi, Tee Garnett, Lauren Oakden-Rayner, Myrtede Alfred, Irvine Sihlahla, Oswa Shafei, Anna Goldenberg

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

2022

Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare.

Viknesh Sounderajah, Melissa D. McCradden, Xiaoxuan Liu, Sherri Rose, Hutan Ashrafian, Gary S. Collins, James A. Anderson, Patrick M. Bossuyt, David Moher, Ara Darzi

Nat. Mach. Intell., 2022

The silent trial - the bridge between bench-to-bedside clinical AI applications.

Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard

Frontiers Digit. Health, 2022

An integration engineering framework for machine learning in healthcare.

Azadeh Assadi, Peter C. Laussen, Andrew J. Goodwin, Sebastian Goodfellow, Will Dixon, Robert W. Greer, Anusha Jegatheeswaran, Devin Singh, Melissa D. McCradden, Sara N. Gallant, Anna Goldenberg, Danny Eytan, Mjaye L. Mazwi

Frontiers Digit. Health, 2022

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022).

Arman Rahmim, Tyler J. Bradshaw, Irène Buvat, Joyita Dutta, Abhinav K. Jha, Paul E. Kinahan, Quanzheng Li, Chi Liu, Melissa D. McCradden, Babak Saboury, Eliot L. Siegel, John J. Sunderland, Richard L. Wahl

CoRR, 2022

How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.

Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg

Proceedings of the Conference on Health, Inference, and Learning, 2022

2020

Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.

Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul

J. Am. Medical Informatics Assoc., 2020

When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning.

Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.

Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg

Proceedings of the Machine Learning for Healthcare Conference, 2019