Dr Melissa McCradden
Externally-Funded Senior Research Fellow
School of Computer Science and Information Technology
College of Engineering and Information Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
Dr. Melissa McCradden is the Artificial Intelligence Director and Deputy Research Director with the Women's and Children's Health Network (WCHN). She is a Deputy Director and The Hospital Research Foundation (THRF) Group Fellow at the Australian Institute for Machine Learning (University of Adelaide). She holds an Adjunct Scientist appointment with the SickKids Research Institute and serves as a member of the SickKids Research Ethics Board in Toronto, Canada. Dr McCradden is an Associate Editor for the journal Research Ethics and is on the Advisory Board for the journal Patterns. She is a member of the World Health Organisation(WHO)/ITU's Focus Group on Clinical Evaluation of AI for Health (FG-AI4H).Dr. McCradden's expertise is in the development of ethical frameworks derived from clinical and technical knowledge grounded in policy, law, and moral theory. She has published on algorithmic bias, responsible clinical evaluation of healthcare machine learning, and clinical integration of AI in journals such as Nature Medicine, JAMA, Lancet Digital Health, JAMIA, and NEJM-AI. Dr. McCradden participates in a plethora of international reporting guideline initiatives including CONSORT and SPIRIT AI (clinical trials), DECIDE-AI (first-in-human trials) and many other international efforts in enhancing regulatory science for health AI. She is listed among the 100 Brilliant Women in AI Ethics and was a Top 40 Under 40 Finalist by InDaily SA (2025).Dr. McCradden holds a PhD in Neuroscience from McMaster University, a Master of Health Sciences in Bioethics from the University of Toronto, and was the inaugural Postdoctoral Fellow in AI Ethics at SickKids and Vector Institute, jointly trained in computer science and bioethics.
Dr. McCradden's work focuses on evidence-based frameworks for the ethical evaluation of novel technologies, particularly in real-world applications in hospital and community health settings. She employs both qualitative and quantitative methodologies to explore the most imminent ethical challenges at the edge of emerging technological frontiers. Her goal in all of her work is to develop and promote practices that enable robust evidence standards to safeguard equity and compassion in healthcare.
Current projects include
Project CANAIRI: https://www.adelaide.edu.au/aiml/our-key-initiatives/project-canairi
Youths' perspectives on AI (study completed in Canada, now initiated in Australia): https://healthydebate.ca/2021/11/topic/children-ai-health-care/
Promoting health AI literacy using co-design and strengths-based learning among Australian consumers
| Date | Position | Institution name |
|---|---|---|
| 2025 - ongoing | Deputy Research Director | Women's and Children's Health Network |
| 2024 - ongoing | Deputy Director | Australian Institute for Machine Learning |
| 2024 - ongoing | THRF Clinical Research Fellow | Australian Institute for Machine Learning |
| 2024 - ongoing | Adjunct Scientist | SickKids Research Institute |
| 2024 - ongoing | AI Director | Women's and Children's Hospital Network |
| 2022 - 2024 | Associate Scientist | SickKids Research Institute |
| 2022 - 2024 | John and Melinda Thompson Director of AI in Medicine | The Hospital for Sick Children (SickKids) |
| 2020 - 2023 | Assistant Professor | University of Toronto |
| 2019 - 2024 | Bioethicist | The Hospital for Sick Children |
| Language | Competency |
|---|---|
| French | Can read, write, speak, understand spoken and peer review |
| Date | Institution name | Country | Title |
|---|---|---|---|
| McMaster University | Canada | PhD | |
| University of Toronto | Canada | MHSc |
| Date | Title | Institution | Country |
|---|---|---|---|
| 2017 - 2018 | Postdoctoral fellow in neurosurgery and injury prevention | Unity Health Toronto | Canada |
| AI Ethics Fellow | Vector Institute/SickKids | Canada |
| Year | Citation |
|---|---|
| 2025 | Laws, E., Palmer, J., Alderman, J., Sharma, O., Ngai, V., Salisbury, T., . . . Liu, X. (2025). Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review. Clinical Imaging, 118, 44 pages. Scopus6 WoS6 Europe PMC6 |
| 2025 | Alderman, J. E., Palmer, J., Laws, E., McCradden, M. D., Ordish, J., Ghassemi, M., . . . Liu, X. (2025). Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations. The Lancet Digital Health, 7(1), e64-e88. Scopus45 WoS39 Europe PMC30 |
| 2025 | Alderman, J. E., Palmer, J., Laws, E., McCradden, M. D., Ordish, J., Ghassemi, M., . . . Liu, X. (2025). Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations. NEJM AI, 2(1). |
| 2025 | Morley, J., Hine, E., Roberts, H., Sirbu, R., Ashrafian, H., Blease, C., . . . Floridi, L. (2025). Global Health in the Age of AI: Charting a Course for Ethical Implementation and Societal Benefit. MINDS AND MACHINES, 35(3), 35 pages. Scopus1 WoS1 |
| 2025 | Laws, E., Palmer, J., Alderman, J., Sharma, O., Ngai, V., Salisbury, T., . . . Liu, X. (2025). Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369] (Clinical Imaging (2025) 118, (S0899707124002997), (10.1016/j.clinimag.2024.110369)). Clinical Imaging, 125, 4 pages. |
| 2025 | Collins, G. S., Moons, K. G. M., Dhiman, P., Riley, R. D., Beam, A. L., Calster, B. V., . . . Logullo, P. (2025). TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation.. Ewha Med J, 48(3), e48. WoS3 Europe PMC2 |
| 2025 | Huo, B., Collins, G. S., Chartash, D., Thirunavukarasu, A. J., Flanagin, A., Iorio, A., . . . Guyatt, G. H. (2025). Reporting Guideline for Chatbot Health Advice StudiesThe CHART Statement. JAMA NETWORK OPEN, 8(8), 14 pages. Scopus3 WoS3 Europe PMC2 |
| 2025 | Huo, B., Collins, G., Chartash, D., Thirunavukarasu, A., Flanagin, A., Iorio, A., . . . Guyatt, G. (2025). Reporting guideline for Chatbot Health Advice studies: the CHART statement. BMC Medicine, 23(1), 447. |
| 2025 | Huo, B., Collins, G., Chartash, D., Thirunavukarasu, A., Flanagin, A., Iorio, A., . . . Guyatt, G. (2025). Reporting guideline for chatbot health advice studies: the Chatbot Assessment Reporting Tool (CHART) statement. BJS-BRITISH JOURNAL OF SURGERY, 112(8), 10 pages. |
| 2025 | Huo, B., Thirunavukarasu, A. J., Collins, G. S., Chartash, D., Flanagin, A., Iorio, A., . . . Guyatt, G. (2025). Reporting guidelines for chatbot health advice studies: explanation and elaboration for the Chatbot Assessment Reporting Tool (CHART). BMJ, 390, 19 pages. Scopus4 WoS8 Europe PMC5 |
| 2025 | Xiao, L., Djordjevic, D., Kang, S., Gonorazky, H., Chiang, J., Ambreen, M., . . . Mccradden, M. D. (2025). Disease-modifying therapies for spinal muscular atrophy: Family experience, ethical considerations, and the role of social determinants of health. JOURNAL OF NEUROMUSCULAR DISEASES, 9 pages. |
| 2025 | Tjoeng, Y. L., Mazwi, M., Goodwin, A., McCradden, M. D., & Chan, T. (2025). Creating Data Systems to Promote Health Equity. Pediatrics, 156(Suppl 1), S109-S115. |
| 2025 | Rafique, D., Liu, X., Gong, B., Belsito, L., McCradden, M. D., Mazwi, M. L., . . . Khalvati, F. (2025). Predicting pediatric diagnostic imaging patient no-show and extended wait-times using LLMs, regression, and tree based models. Frontiers in Artificial Intelligence, 8, 16 pages. |
| 2025 | Huo, B., Collins, G., Chartash, D., Thirunavukarasu, A., Flanagin, A., Iorio, A., . . . Guyatt, G. (2025). Reporting guideline for chatbot health advice studies: the Chatbot Assessment Reporting Tool (CHART) statement. BMJ Medicine, 4(1), e001632. Scopus4 WoS1 |
| 2025 | McCradden, M. D., Mazwi, M. L., & Oakden-Rayner, L. (2025). Can an accurate model be bad?. Patterns, 6(4), 101205. Scopus1 WoS1 Europe PMC1 |
| 2025 | Plummer, K., Pope, N., McCradden, M. D., Ullman, A. J., Foster, M., Stinson, J. N., & Griffin, B. (2025). Harnessing technology in pediatric nursing: Balancing innovation, equity and sustainability. Journal of Pediatric Nursing, 82, A1-A4. |
| 2025 | Laws, E., Charalambides, M., Vadera, S., Keller, E., Alderman, J., Blackboro, B., . . . Liu, X. (2025). Diversity and Inclusion Within Datasets in Heart Failure: A Systematic Review. JACC: Advances, 4(3), 101610. Scopus1 WoS1 |
| 2025 | McCradden, M. D., London, A. J., Gichoya, J. W., Sendak, M., Erdman, L., Stedman, I., . . . Liu, X. (2025). CANAIRI: the Collaboration for Translational Artificial Intelligence Trials in healthcare.. Nat Med, 31(1), 9-11. Scopus7 WoS7 Europe PMC5 |
| 2025 | McCradden, M. D., Thai, K., Assadi, A., Tonekaboni, S., Stedman, I., Joshi, S., . . . Goldenberg, A. (2025). What makes a ‘good’ decision with artificial intelligence? A grounded theory study in paediatric care. BMJ Evidence-Based Medicine, 30(3), 183-193. Scopus1 WoS1 Europe PMC1 |
| 2025 | Moons, K. G. M., Damen, J. A. A., Kaul, T., Hooft, L., Andaur Navarro, C., Dhiman, P., . . . van Smeden, M. (2025). PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods.. BMJ, 388, e082505. Scopus69 WoS55 Europe PMC52 |
| 2025 | Holst, J. J., Schéele, C., Scherer, P. E., Jia, W., Segal, E., Slavov, N., . . . Jacobs, P. G. (2025). Artificial intelligence in metabolic research.. Nat Metab, 7(11), 2183-2186. Europe PMC1 |
| 2025 | Pinto, A. D., Birdi, S., Durant, S., Rabet, R., Parekh, R., Ali, S., . . . Mishra, S. (2025). Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation.. JMIR Public Health Surveill, 11, e68952. |
| 2024 | Birdi, S., Rabet, R., Durant, S., Patel, A., Vosoughi, T., Shergill, M., . . . Pinto, A. D. (2024). Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review. BMC Public Health, 24(1), 16 pages. Scopus3 WoS2 Europe PMC3 |
| 2024 | Kwong, J. C. C., Nguyen, D. -D., Khondker, A., Kim, J. K., Johnson, A. E. W., McCradden, M. M., . . . Rickard, M. (2024). When the Model Trains You: Induced Belief Revision and Its Implications on Artificial Intelligence Research and Patient Care — A Case Study on Predicting Obstructive Hydronephrosis in Children. NEJM AI, 1(2). |
| 2024 | Gath, J., Leung, C., Adebajo, A. O., Beng, J., Arora, A., Alderman, J. E., . . . Liu, X. (2024). Exploring patient and public participation in the STANDING Together initiative for AI in healthcare.. Nature medicine, 30(12), 3406-3408. |
| 2024 | Tikhomirov, L., Semmler, C., McCradden, M., Searston, R., Ghassemi, M., & Oakden-Rayner, L. (2024). Medical artificial intelligence for clinicians: the lost cognitive perspective. The Lancet: Digital Health, 6(8), e589-e594. Scopus20 WoS15 Europe PMC10 |
| 2024 | Martindale, A. P. L., Llewellyn, C. D., de Visser, R. O., Ng, B., Ngai, V., Kale, A. U., . . . Liu, X. (2024). Author Correction: Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.. Nat Commun, 15(1), 6376. Scopus1 WoS1 Europe PMC1 |
| 2024 | Turner, L. M., & McCradden, M. D. (2024). Complexities in Capacity Assessment for Persons with Severe and Enduring Anorexia.. Am J Bioeth, 24(8), 111-113. Scopus1 WoS1 |
| 2024 | McCradden, M. D., & Stedman, I. (2024). Explaining decisions without explainability? Artificial intelligence and medicolegal accountability. Future Healthcare Journal, 11(3), 100171. Europe PMC2 |
| 2024 | Ning, Y., Liu, X., Collins, G. S., Moons, K. G. M., McCradden, M., Ting, D. S. W., . . . Liu, N. (2024). An ethics assessment tool for artificial intelligence implementation in healthcare: CARE-AI. Nature Medicine, 30(11), 2 pages. Scopus12 WoS10 Europe PMC10 |
| 2024 | Alderman, J. E., Charalambides, M., Sachdeva, G., Laws, E., Palmer, J., Lee, E., . . . Liu, X. (2024). Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review. Lancet Digital Health, 6(11), e827-e847. Scopus7 |
| 2024 | Martindale, A. P. L., Ng, B., Ngai, V., Kale, A. U., Ferrante di Ruffano, L., Golub, R. M., . . . Liu, X. (2024). Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines. Nature Communications, 15(1), 1619-1-1619-11. Scopus24 WoS23 Europe PMC19 |
| 2024 | Collins, G. S., Moons, K. G. M., Dhiman, P., Riley, R. D., Beam, A. L., Van Calster, B., . . . Logullo, P. (2024). TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.. BMJ, 385, 14 pages. Scopus1004 WoS854 Europe PMC720 |
| 2024 | Anderson, K. (2024). Andrew Caillard: <i>The Australian Ark</i>:<i> The Story of Australian Wine</i>. JOURNAL OF WINE ECONOMICS, 6(11), 4 pages. WoS7 Europe PMC7 |
| 2024 | Liu, X., Rivera, S. C., Moher, D., Calvert, M. J., Denniston, A. K., Chan, A. W., . . . Rowley, S. (2024). Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Revista Panamericana de Salud Publica/Pan American Journal of Public Health, 48, 15 pages. Scopus2 WoS1 Europe PMC1 |
| 2024 | Rivera, S. C., Liu, X., Chan, A. W., Denniston, A. K., Calvert, M. J., Darzi, A., . . . Rowley, S. (2024). Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Revista Panamericana de Salud Publica/Pan American Journal of Public Health, 48, e12. Scopus1 Europe PMC1 |
| 2024 | Ferretti, A., Adjei, K. K., Ali, J., Atuire, C., Ayuk, B. T., Banougnin, B. H., . . . Vayena, E. (2024). Digital tools for youth health promotion: principles, policies and practices in sub-Saharan Africa. Health Promotion International, 39(2), 11 pages. Scopus3 WoS4 Europe PMC2 |
| 2024 | Jones, C., Castro, D. C., De Sousa Ribeiro, F., Oktay, O., McCradden, M., & Glocker, B. (2024). A causal perspective on dataset bias in machine learning for medical imaging. Nature Machine Intelligence, 6(2), 138-146. Scopus30 WoS21 |
| 2023 | Herington, J., McCradden, M. D., Creel, K., Boellaard, R., Jones, E. C., Jha, A. K., . . . Saboury, B. (2023). Ethical considerations for artificial intelligence in medical imaging: Data collection, development, and evaluation. Journal of Nuclear Medicine, 64(12), 1848-1854. Scopus34 WoS22 Europe PMC21 |
| 2023 | McCradden, M. D., Joshi, S., Anderson, J. A., & London, A. J. (2023). A normative framework for artificial intelligence as a sociotechnical system in healthcare. Patterns, 4(11), 9 pages. Scopus14 WoS13 Europe PMC6 |
| 2023 | Herington, J., McCradden, M. D., Creel, K., Boellaard, R., Jones, E. C., Jha, A. K., . . . Saboury, B. (2023). Ethical Considerations for Artificial Intelligence in Medical Imaging: Deployment and Governance. Journal of Nuclear Medicine, 64(10), 1509-1515. Scopus35 WoS24 Europe PMC25 |
| 2023 | Kwong, J. C. C., Khondker, A., Lajkosz, K., McDermott, M. B. A., Frigola, X. B., McCradden, M. D., . . . Johnson, A. E. W. (2023). APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support. JAMA Network Open, 6(9), 11 pages. Scopus67 WoS56 Europe PMC52 |
| 2023 | McCradden, M. D. (2023). Ethics, First. American Journal of Bioethics, 23(9), 55-56. |
| 2023 | Dhiman, P., Whittle, R., Van Calster, B., Ghassemi, M., Liu, X., McCradden, M. D., . . . Collins, G. S. (2023). The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nature Machine Intelligence, 5(8), 816-817. Scopus9 WoS11 |
| 2023 | McCradden, M., Hui, K., & Buchman, D. Z. (2023). Evidence, ethics and the promise of artificial intelligence in psychiatry. Journal of Medical Ethics, 49(8), 573-579. Scopus65 WoS49 Europe PMC38 |
| 2023 | Xiao, L., Kang, S., Djordjevic, D., Gonorazky, H., Chiang, J., Ambreen, M., . . . Amin, R. (2023). Understanding caregiver experiences with disease-modifying therapies for spinal muscular atrophy: A qualitative study. Archives of Disease in Childhood, 108(11), 929-934. Scopus8 WoS8 Europe PMC8 |
| 2023 | Bradshaw, T. J., McCradden, M. D., Jha, A. K., Dutta, J., Saboury, B., Siegel, E. L., & Rahmim, A. (2023). Artificial Intelligence Algorithms Need to Be Explainable—or Do They?. Journal of Nuclear Medicine, 64(6), 976-977. Scopus11 WoS7 Europe PMC7 |
| 2023 | Katzman, D. K., & McCradden, M. D. (2023). Capacity for Preferences: Adolescents With AN-PLUS. Journal of Adolescent Health, 72(6), 827-828. Scopus3 WoS2 Europe PMC2 |
| 2023 | Taheri-Shirazi, M., Namdar, K., Ling, K., Karmali, K., McCradden, M. D., Lee, W., & Khalvati, F. (2023). Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning. Frontiers in Public Health, 11, 968319. Scopus5 WoS4 Europe PMC4 |
| 2023 | McCradden, M. D., & Kirsch, R. E. (2023). Patient wisdom should be incorporated into health AI to avoid algorithmic paternalism. Nature Medicine, 29(4), 765-766. Scopus16 WoS13 Europe PMC11 |
| 2023 | Tsiandoulas, K., McSheffrey, G., Fleming, L., Rawal, V., Fadel, M. P., Katzman, D. K., & McCradden, M. D. (2023). Ethical tensions in the treatment of youth with severe anorexia nervosa. The Lancet Child and Adolescent Health, 7(1), 69-76. Scopus15 WoS13 Europe PMC11 |
| 2023 | Arora, A., Alderman, J. E., Palmer, J., Ganapathi, S., Laws, E., McCradden, M. D., . . . Liu, X. (2023). The value of standards for health datasets in artificial intelligence-based applications. Nature Medicine, 29(11), 2929-2938. Scopus164 WoS131 Europe PMC106 |
| 2023 | Thai, K., Tsiandoulas, K. H., Stephenson, E. A., Menna-Dack, D., Zlotnik Shaul, R., Anderson, J. A., . . . McCradden, M. D. (2023). Perspectives of Youths on the Ethical Use of Artificial Intelligence in Health Care Research and Clinical Care. JAMA network open, 6(5), 10 pages. Scopus33 WoS29 Europe PMC17 |
| 2023 | McCradden, M. D. (2023). Partnering with children and youth to advance artificial intelligence in healthcare. Pediatric Research, 93(2), 284-286. Scopus2 WoS2 Europe PMC1 |
| 2023 | Cruz Rivera, S., Liu, X., Chan, A. -W., Denniston, A. K., Calvert, M. J., Grupo de Trabajo SPIRIT-AI y CONSORT-AI., . . . Grupo de Consenso SPIRIT-AI y CONSORT-AI. (2023). [Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI].. Revista panamericana de salud publica = Pan American journal of public health, 47, e149. Europe PMC1 |
| 2022 | Anderson, J. A., McCradden, M. D., & Stephenson, E. A. (2022). Response to Open Peer Commentaries: On Social Harms, Big Tech, and Institutional Accountability. American Journal of Bioethics, 22(10), W6-W8. Scopus1 WoS1 Europe PMC1 |
| 2022 | McCradden, M. D., Anderson, J. A., A. Stephenson, E., Drysdale, E., Erdman, L., Goldenberg, A., & Zlotnik Shaul, R. (2022). A Research Ethics Framework for the Clinical Translation of Healthcare Machine Learning. American Journal of Bioethics, 22(5), 8-22. Scopus84 WoS70 Europe PMC56 |
| 2022 | Sounderajah, V., McCradden, M. D., Liu, X., Rose, S., Ashrafian, H., Collins, G. S., . . . Darzi, A. (2022). Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. Nature Machine Intelligence, 4(4), 316-317. Scopus11 WoS8 |
| 2022 | McCradden, M. (2022). Melissa McCradden. CELL REPORTS MEDICINE, 3(12), 2 pages. |
| 2022 | Liu, X., Glocker, B., McCradden, M. M., Ghassemi, M., Denniston, A. K., & Oakden-Rayner, L. (2022). The medical algorithmic audit (vol 4, pg e384, 2022). LANCET DIGITAL HEALTH, 4(6), E405. |
| 2022 | Kwong, J. C. C., Erdman, L., Khondker, A., Skreta, M., Goldenberg, A., McCradden, M. D., . . . Rickard, M. (2022). The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers in Digital Health, 4, 10 pages. Scopus33 WoS30 Europe PMC21 |
| 2022 | Assadi, A., Laussen, P. C., Goodwin, A. J., Goodfellow, S., Dixon, W., Greer, R. W., . . . Mazwi, M. L. (2022). An integration engineering framework for machine learning in healthcare. Frontiers in Digital Health, 4, 12 pages. Scopus14 WoS9 Europe PMC8 |
| 2022 | Pereira, M., Akinkugbe, O., Buckley, L., Gilfoyle, E., Ibrahim, S., McCradden, M., . . . Dryden-Palmer, K. (2022). Up to the Challenge: Adapting Pediatric Intensive Care During a Global Pandemic. Frontiers in Pediatrics, 10, 10 pages. Scopus4 WoS3 Europe PMC3 |
| 2022 | Monah, S. R., Wagner, M. W., Biswas, A., Khalvati, F., Erdman, L. E., Amirabadi, A., . . . Ertl-Wagner, B. B. (2022). Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence. Pediatric Radiology, 52(11), 2111-2119. Scopus12 WoS10 Europe PMC5 |
| 2022 | Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., . . . Mcculloch, P. (2022). Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. The BMJ, 377, e070904. Scopus178 WoS385 Europe PMC133 |
| 2022 | Liu, X., Glocker, B., McCradden, M. M., Ghassemi, M., Denniston, A. K., & Oakden-Rayner, L. (2022). The medical algorithmic audit.. Lancet Digit Health, 4(5), E384-E397. Scopus165 WoS144 Europe PMC103 |
| 2022 | Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., . . . Militello, L. (2022). Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (Nature Medicine, (2022), 28, 5, (924-933), 10.1038/s41591-022-01772-9). Nature Medicine, 28(10), 2218. Scopus8 WoS2 Europe PMC3 |
| 2022 | Ganapathi, S., Palmer, J., Alderman, J. E., Calvert, M., Espinoza, C., Gath, J., . . . Liu, X. (2022). Tackling bias in AI health datasets through the STANDING Together initiative.. Nature medicine, 28(11), 2232-2233. Scopus61 WoS60 Europe PMC52 |
| 2022 | Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., . . . Yoon, J. H. (2022). Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nature Medicine, 28(5), 924-933. Scopus308 WoS44 Europe PMC254 |
| 2021 | Baba, A., Saha, A., McCradden, M. D., Boparai, K., Zhang, S., Pirouzmand, F., . . . Cusimano, M. D. (2021). Development and validation of a patient-centered, meningioma-specific quality-of-life questionnaire. Journal of Neurosurgery, 135(6), 1685-1694. Scopus12 WoS10 Europe PMC10 |
| 2021 | McCradden, M. D., & Chad, L. (2021). Screening for facial differences worldwide: equity and ethics. The Lancet Digital Health, 3(10), e615-e616. Scopus2 WoS2 Europe PMC1 |
| 2021 | Sounderajah, V., Ashrafian, H., Rose, S., Shah, N. H., Ghassemi, M., Golub, R., . . . Darzi, A. (2021). A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI. Nature Medicine, 27(10), 1663-1665. Scopus159 WoS149 Europe PMC134 |
| 2021 | McCradden, M. D. (2021). When is accuracy off-target?. Translational Psychiatry, 11(1), 369. Scopus8 WoS8 Europe PMC5 |
| 2021 | Zlotnik Shaul, R., Shaul, D., Anderson, J., & McCradden, M. (2021). The Gift in Precision Medicine: Unwrapping the Significance of Reciprocity and Generosity. American Journal of Bioethics, 21(4), 78-80. Scopus2 WoS4 Europe PMC2 |
| 2021 | Helmers, A., McCradden, M., Kirsch, R., & Shaul, R. Z. (2021). Cracking the Code: COVID-19 and the Future of Professional Promises. American Journal of Bioethics, 21(1), 19-21. |
| 2021 | McCradden, M. D., Patel, E., & Chad, L. (2021). The point-of-care use of a facial phenotyping tool in the genetics clinic: An ethics tête-a-tête. American Journal of Medical Genetics, Part A, 185(2), 658-660. Scopus7 WoS7 Europe PMC3 |
| 2021 | Shergill, M., Durant, S., Birdi, S., Rabet, R., Ziegler, C., Ali, S., . . . Pinto, A. D. (2021). Machine learning used to study risk factors for chronic diseases: A scoping review. CANADIAN JOURNAL OF PUBLIC HEALTH-REVUE CANADIENNE DE SANTE PUBLIQUE, 15 pages. Scopus3 WoS3 Europe PMC1 |
| 2020 | McCradden, M. D., Joshi, S., Anderson, J. A., Mazwi, M., Goldenberg, A., & Shaul, R. Z. (2020). Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning. Journal of the American Medical Informatics Association, 27(12), 2024-2027. Scopus78 WoS59 Europe PMC44 |
| 2020 | McCradden, M. D., Baba, A., Saha, A., Ahmad, S., Boparai, K., Fadaiefard, P., & Cusimano, M. D. (2020). Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a qualitative study. CMAJ open, 8(1), E90-E95. Scopus70 Europe PMC47 |
| 2020 | McCradden, M. D., Sarker, T., & Paprica, P. A. (2020). Conditionally positive: A qualitative study of public perceptions about using health data for artificial intelligence research. BMJ Open, 10(10), e039798. Scopus55 WoS52 Europe PMC42 |
| 2020 | McCradden, M. D., Anderson, J. A., & Zlotnik Shaul, R. (2020). Accountability in the Machine Learning Pipeline: The Critical Role of Research Ethics Oversight. American Journal of Bioethics, 20(11), 40-42. Scopus8 WoS9 Europe PMC4 |
| 2020 | McCradden, M. D., Stephenson, E. A., & Anderson, J. A. (2020). Clinical research underlies ethical integration of healthcare artificial intelligence. Nature Medicine, 26(9), 1325-1326. Scopus61 WoS51 Europe PMC37 |
| 2020 | McCradden, M. D., Joshi, S., Mazwi, M., & Anderson, J. A. (2020). Ethical limitations of algorithmic fairness solutions in health care machine learning. The Lancet Digital Health, 2(5), e221-e223. Scopus170 WoS141 Europe PMC117 |
| 2020 | Baba, A., McCradden, M. D., Rabski, J., & Cusimano, M. D. (2020). Determining the unmet needs of patients with intracranial meningioma - A qualitative assessment. Neuro-Oncology Practice, 7(2), 228-238. Scopus12 WoS13 |
| 2020 | Cruz Rivera, S., Liu, X., Chan, A. W., Denniston, A. K., Calvert, M. J., Darzi, A., . . . Rowley, S. (2020). Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Nature Medicine, 26(9), 1351-1363. Scopus381 Europe PMC288 |
| 2020 | Cruz Rivera, S., Liu, X., Chan, A. W., Denniston, A. K., Calvert, M. J., Ashrafian, H., . . . Yau, C. (2020). Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. The Lancet Digital Health, 2(10), e549-e560. Scopus264 Europe PMC177 |
| 2020 | Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., Ashrafian, H., . . . Yau, C. (2020). Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. The Lancet Digital Health, 2(10), e537-e548. Scopus254 Europe PMC201 |
| 2020 | Rivera, S. C., Liu, X., Chan, A. -W., Denniston, A. K., Calvert, M. J., Ashrafian, H., . . . Yau, C. (2020). Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension. BMJ-BRITISH MEDICAL JOURNAL, 370, 14 pages. WoS45 Europe PMC161 |
| 2020 | Liu, X., Rivera, S. C., Moher, D., Calvert, M. J., Denniston, A. K., Ashrafian, H., . . . Yau, C. (2020). Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension. BMJ-BRITISH MEDICAL JOURNAL, 370, 13 pages. WoS67 Europe PMC217 |
| 2020 | Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., Chan, A. W., . . . Rowley, S. (2020). Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Nature Medicine, 26(9), 1364-1374. Scopus594 Europe PMC480 |
| 2019 | McCradden, M. D., Vasileva, D., Orchanian-Cheff, A., & Buchman, D. Z. (2019). Ambiguous identities of drugs and people: A scoping review of opioid-related stigma. International Journal of Drug Policy, 74, 205-215. Scopus108 WoS100 Europe PMC89 |
| 2019 | McCradden, M. D., & Anderson, J. A. (2019). The Last Refuge of Privacy. AJOB Neuroscience, 10(1), 25-28. |
| 2019 | McCradden, M. D., & Cusimano, M. D. (2019). Staying true to Rowan’s Law: how changing sport culture can realize the goal of the legislation. Canadian Journal of Public Health, 110(2), 165-168. Scopus15 WoS13 Europe PMC7 |
| 2019 | McCradden, M. D., & Cusimano, M. D. (2019). Voices of survivors: 'you will not destroy our light'. British Journal of Sports Medicine, 53(22), 1384-1385. Scopus6 WoS4 Europe PMC2 |
| 2018 | McCradden, M. D., & Cusimano, M. D. (2018). Concussions in sledding sports and the unrecognized "sled head": A systematic review. Frontiers in Neurology, 9(SEP), 8 pages. Scopus16 WoS12 |
| 2018 | McCradden, M. D., & Cusimano, M. D. (2018). Optimized or Hijacked? The Moral Boundaries of Natural Athletic Performance. American Journal of Bioethics, 18(6), 26-28. Scopus1 WoS1 Europe PMC1 |
| 2018 | McCradden, M. D., & Cusimano, M. D. (2018). Questioning Assumptions About Vulnerability in Psychiatric Patients. AJOB Neuroscience, 9(4), 221-223. |
| Year | Citation |
|---|---|
| 2023 | Mccradden, M., Odusi, O., Joshi, S., Akrout, I., Ndlovu, K., Glocker, B., . . . Goldenberg, A. (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. In 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 15 pages). Online: ACM. DOI Scopus17 WoS17 |
| 2023 | Xiao, L., Kang, S., Gonorazky, H., Chiang, J., Ambreen, M., Weinstock, L., . . . Amin, R. (2023). Understanding the Experiences of Caregivers of Children With Spinal Muscular Atrophy in the Era of Disease-modifying Therapies. In AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE Vol. 207 (pp. 2 pages). DC, Washington: AMER THORACIC SOC. |
| 2022 | Tonekaboni, S., Morgenshtern, G., Assadi, A., Pokhrel, A., Huang, X., Jayarajan, A., . . . Goldenberg, A. (2022). How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. In Proceedings of Machine Learning Research Vol. 174 (pp. 169-182). ELECTR NETWORK: JMLR-JOURNAL MACHINE LEARNING RESEARCH. Scopus7 WoS6 |
| 2020 | McCradden, M., Mazwi, M., Joshi, S., & Anderson, J. A. (2020). When Your Only Tool Is A Hammer Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning. In PROCEEDINGS OF THE 3RD AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY AIES 2020 (pp. 109). NY, New York: ASSOC COMPUTING MACHINERY. DOI WoS3 |
| 2019 | Tonekaboni, S., Joshi, S., McCradden, M. D., & Goldenberg, A. (2019). What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. In J. Fackler, K. Jung, D. Kale, R. Ranganath, B. Wallace, J. Wiens, & F. Doshi-Velez (Eds.), Proceedings of Machine Learning Research Vol. 106 (pp. 359-380). MI, Ann Arbor: JMLR-JOURNAL MACHINE LEARNING RESEARCH. Scopus348 WoS280 |
| Year | Citation |
|---|---|
| 2025 | McCradden, M., Tng, S., Jeyaseelan, D., Leane, C., Campbell, M., Braund, T., . . . Tang, J. (2025). A medical algorithmic audit framework for evaluating the safety, equity, and quality of an AI Scribe tool in a paediatric developmental assessment clinic. DOI |
| 2020 | McCradden, M., Sarker, T., & Paprica, A. (2020). Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research. DOI |
The Hospital Research Foundation Group Fellowship Grant
Centre for Augmented Reasoning, Australian Institute for Machine Learning
Canadian Institutes for Health Research
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2025 | Principal Supervisor | Ethics of AI in Healthcare | Doctor of Philosophy | Doctorate | Full Time | Mr Humphrey Thompson |
| 2025 | Principal Supervisor | Ethics of AI in Healthcare | Doctor of Philosophy | Doctorate | Full Time | Mr Humphrey Thompson |
| 2024 | Co-Supervisor | Understanding Bias Caused by User Interaction with AI in High-Risk Decision Making | Doctor of Philosophy | Doctorate | Full Time | Miss Lana Tikhomirov |
| 2024 | Co-Supervisor | Understanding Bias Caused by User Interaction with AI in High-Risk Decision Making | Doctor of Philosophy | Doctorate | Full Time | Miss Lana Tikhomirov |
| Date | Role | Membership | Country |
|---|---|---|---|
| 2025 - ongoing | Member | Sigma Xi Scientific Research Honor Society | United States |