Melissa D. McCradden

16 papers C 1Journal 12Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Can an accurate model be bad?
Patterns
Melissa D. McCradden, Mjaye L. Mazwi, Lauren Oakden-Rayner
2025 J jnl
Global Health in the Age of AI: Charting a Course for Ethical Implementation and Societal Benefit.
Minds Mach.
Jessica Morley, Emmie Hine, Huw Roberts, Renee Sirbu, Hutan Ashrafian, Charlotte Blease, Marisha Boyd, John L. Chen, Alexandre Chiavegatto Filho, Enrico W. Coiera, Glenn I. Cohen, Amelia Fiske, Nandini Jayakumar, Angeliki Kerasidou, Federica Mandreoli, Melissa D. McCradden, Stella Namuganza, Elaine O. Nsoesie, Ravi B. Parikh, Sandeep Reddy, Jana Sedlakova, Tamara Sunbul, Sophie van Baalen, Hannah van Kolfschooten, Luciano Floridi
2025 J jnl
Predicting pediatric diagnostic imaging patient no-show and extended wait-times using LLMs, regression, and tree based models.
Frontiers Artif. Intell.
Daniel Rafique, Xuan Liu, Bo Gong, Laura Belsito, Melissa D. McCradden, Mjaye L. Mazwi, Wayne Lee, Graham Ohanlon, Kyle Tsang, Manohar Shroff, Birgit Ertl-Wagner, Farzad Khalvati
2023 J jnl
A normative framework for artificial intelligence as a sociotechnical system in healthcare.
Patterns
Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London
2023 J jnl
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging.
CoRR
Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker
2023 J jnl
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols.
Nat. Mac. Intell.
Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins
2023 — conf
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
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
2022 J jnl
An integration engineering framework for machine learning in healthcare.
Frontiers Digit. Health
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
2022 J jnl
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare.
Nat. Mach. Intell.
Viknesh Sounderajah, Melissa D. McCradden, Xiaoxuan Liu, Sherri Rose, Hutan Ashrafian, Gary S. Collins, James A. Anderson, Patrick M. Bossuyt, David Moher, Ara Darzi
2022 — conf
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.
CHIL
Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg
2022 J jnl
Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022).
CoRR
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
2022 J jnl
The silent trial - the bridge between bench-to-bedside clinical AI applications.
Frontiers Digit. Health
Jethro C. C. Kwong, Lauren Erdman, Adree Khondker, Marta Skreta, Anna Goldenberg, Melissa D. McCradden, Armando J. Lorenzo, Mandy Rickard
2020 J jnl
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.
J. Am. Medical Informatics Assoc.
Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Anna Goldenberg, Randi Zlotnik Shaul
2020 C conf
When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning.
AIES
Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson
2019 — conf
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.
MLHC
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg
2019 J jnl
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.
CoRR
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg