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ORCIDMelissa D. McCradden
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2020 – today
- 2023
[j6]Paula Dhiman
, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins:
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nat. Mac. Intell. 5(8): 816-817 (2023)- [j5]Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London:
A normative framework for artificial intelligence as a sociotechnical system in healthcare. Patterns 4(11): 100864 (2023) - [c4]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:
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. FAccT 2023: 1505-1519 - [i3]Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker:
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging. CoRR abs/2307.16526 (2023) - 2022
- [j4]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:
An integration engineering framework for machine learning in healthcare. Frontiers Digit. Health 4 (2022) - [j3]Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard:
The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers Digit. Health 4 (2022) - [j2]Viknesh Sounderajah, Melissa D. McCradden, Xiaoxuan Liu, Sherri Rose, Hutan Ashrafian, Gary S. Collins, James A. Anderson, Patrick M. Bossuyt, David Moher, Ara Darzi:
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. Nat. Mach. Intell. 4(4): 316-317 (2022) - [c3]Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg:
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. CHIL 2022: 169-182 - [i2]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:
Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022). CoRR abs/2211.03783 (2022) - 2020
- [j1]Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul:
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. J. Am. Medical Informatics Assoc. 27(12): 2024-2027 (2020) - [c2]Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson:
When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning. AIES 2020: 109
2010 – 2019
- 2019
- [c1]Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg:
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. MLHC 2019: 359-380 - [i1]Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg:
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. CoRR abs/1905.05134 (2019)
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