Melissa McCradden

Dr Melissa McCradden

THRF Clinical Research Fellow

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and 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, and a Deputy Director and The Hospital Research Foundation (THRF) Group Fellow at the Australian Institute for Machine Learning at the University of Adelaide. She is an Adjunct Scientist with the SickKids Research Institute and member of the SickKids Research Ethics Board in Toronto, Canada. Dr McCradden serves as an Associate Editor for the journal Research Ethics and on the Advisory Board for the journal Patterns.

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 major international consortia such as the World Health Organization's Clinical Evaluation Task Force for AI in Healthcare. She is listed among the 100 Brilliant Women in AI Ethics.

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.

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

  • Appointments
    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 Competencies
    Language Competency
    French Can read, write, speak, understand spoken and peer review

  • Education
    Date Institution name Country Title
    McMaster University Canada PhD
    University of Toronto Canada MHSc

  • Postgraduate Training
    Date Title Institution Country
    2017 - 2018 Postdoctoral fellow in neurosurgery and injury prevention Unity Health Toronto Canada
    AI Ethics Fellow Vector Institute/SickKids Canada

  • Journals
    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.
    DOI Scopus1 Europe PMC1
    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.
    DOI Scopus3 Europe PMC3
    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).
    DOI
    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.
    DOI Scopus1
    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, 11 pages.
    DOI
    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 (Clinical research ed.), 388, e082505.
    DOI
    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.
    DOI
    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).
    DOI
    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.
    DOI
    2024 Shah, J., Poirier, B. F., Hedges, J., Jamieson, L., & Sethi, S. (2024). Effect of sleep on oral health: A scoping review. Sleep Medicine Reviews, 76, 12 pages.
    DOI Scopus1 Europe PMC1
    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.
    DOI Scopus3 Europe PMC1
    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.
    DOI
    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.
    DOI
    2024 McCradden, M. D., & Stedman, I. (2024). Explaining decisions without explainability? Artificial intelligence and medicolegal accountability.. Future healthcare journal, 11(3), 100171.
    DOI
    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.
    DOI Scopus2 Europe PMC1
    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. The Lancet Digital Health, 6(11), e827-e847.
    DOI Scopus2
    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, 1.
    DOI Scopus1
    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, 1.
    DOI
    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.
    DOI
    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.
    DOI Scopus10
    2024 Suryawanshi, U. P., Ghorpade, U. V., Yuwono, J. A., Kumar, P. V., Gaikwad, M. A., Shin, S. W., . . . Kim, J. H. (2024). Cr-dopant induced crystal orientation and shape modulation in Ni<sub>2</sub>P nanocrystals for improving electrosynthesis of methanol to formate coupled with hydrogen production. Journal of Materials Chemistry A, 12(25), 15127-15136.
    DOI Scopus2
    2024 Kurdi, A., Degnah, A., Juri, A. Z., Ghani, J. A., & Basak, A. K. (2024). Deformation behavior of the hybrid S-phase layer formed on a stainless-steel substrate by thermochemical heat treatment under mechanical loading. Materials Science and Engineering: A, 900, 146462.
    DOI Scopus3
    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.
    DOI Scopus256 Europe PMC154
    2024 Shearer, H. L., Currie, M. J., Agnew, H. N., Trappetti, C., Stull, F., Pace, P. E., . . . Dickerhof, N. (2024). Hypothiocyanous acid reductase is critical for host colonization and infection by Streptococcus pneumoniae.. J Biol Chem, 300(5), 107282.
    DOI
    2024 Lowe-Jones, R., Ethier, I., Fisher, L. A., Wong, M. M. Y., Thompson, S., Nakhoul, G., . . . Zaidi, D. (2024). Capacity for the management of kidney failure in the International Society of Nephrology North America and the Caribbean region: report from the 2023 ISN Global Kidney Health Atlas (ISN-GKHA). Kidney International Supplements, 13(1), 83-96.
    DOI Scopus1
    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.
    DOI Europe PMC1
    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.
    DOI Scopus6 Europe PMC3
    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.
    DOI Scopus68 WoS2 Europe PMC40
    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.
    DOI Scopus12 Europe PMC3
    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.
    DOI Scopus5 Europe PMC1
    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.
    DOI Scopus16 Europe PMC6
    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.
    DOI Scopus32 Europe PMC11
    2023 McCradden, M. D. (2023). Ethics, First. American Journal of Bioethics, 23(9), 55-56.
    DOI
    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.
    DOI Scopus5
    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.
    DOI Scopus38 Europe PMC16
    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.
    DOI Scopus6 Europe PMC4
    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.
    DOI Scopus7 Europe PMC1
    2023 Katzman, D. K., & McCradden, M. D. (2023). Capacity for Preferences: Adolescents With AN-PLUS. Journal of Adolescent Health, 72(6), 827-828.
    DOI Scopus2 Europe PMC1
    2023 McCradden, M. D. (2023). Partnering with children and youth to advance artificial intelligence in healthcare. Pediatric Research, 93(2), 284-286.
    DOI Scopus2 Europe PMC1
    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, 11 pages.
    DOI Scopus4 Europe PMC3
    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.
    DOI Scopus9 Europe PMC4
    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.
    DOI Scopus10 Europe PMC5
    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.
    DOI Scopus18 WoS2 Europe PMC8
    2022 McCradden, M. (2022). Melissa McCradden. CELL REPORTS MEDICINE, 3(12), 2 pages.
    DOI
    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.
    DOI
    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.
    DOI Scopus16
    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.
    DOI Scopus11
    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.
    DOI Scopus4
    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.
    DOI Scopus8 Europe PMC3
    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.
    DOI Scopus112 Europe PMC58
    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.
    DOI
    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.
    DOI Scopus66 Europe PMC24
    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.
    DOI Scopus10
    2022 Shi, P., Liu, Z. -Y., Zhang, X. -Q., Chen, X., Yao, N., Xie, J., . . . Zhang, Q. (2022). Polar interaction of polymer host-solvent enables stable solid electrolyte interphase in composite lithium metal anodes. JOURNAL OF ENERGY CHEMISTRY, 64, 172-178.
    DOI WoS39
    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.
    DOI Scopus127 WoS37 Europe PMC54
    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.
    DOI Scopus3 Europe PMC2
    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.
    DOI Scopus45 WoS5 Europe PMC26
    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.
    DOI Scopus214 Europe PMC147
    2021 Chen, B., Gao, H., Li, H., Ma, H., Gao, P., Chu, P., & Shi, P. (2021). Indoor and Outdoor Surface Measurement of 3D Objects under Different Background Illuminations and Wind Conditions Using Laser-Beam-Based Sinusoidal Fringe Projections. PHOTONICS, 8(6), 17 pages.
    DOI WoS3
    2021 Chen, B., Li, H., Yue, J., & Shi, P. (2021). Fourier-Transform-Based Surface Measurement and Reconstruction of Human Face Using the Projection of Monochromatic Structured Light. SENSORS, 21(7), 14 pages.
    DOI WoS3
    2021 Liu, S., Shi, P., Wan, Z., Lu, S., Lv, J., & Meng, F. (2021). Interrelationships between Acoustic Emission and Cutting Force in Rock Cutting. GEOFLUIDS, 2021, 12 pages.
    DOI WoS1
    2021 Yin, J., Gao, C., Zhu, M., Wang, H., Shi, P., Chen, Y. Y., . . . Yu, B. (2021). Oil Accumulation Model and Its Main Controlling Factors in Lower Yanchang Formation, Wuqi-Dingbianarea, Ordos Basin, China. GEOFLUIDS, 2021, 10 pages.
    DOI WoS2
    2021 Dey, R. K., Basak, A., Ray, S., & Sarkar, T. (2021). Newly Born Extragalactic Millisecond Pulsars as Efficient Emitters of PeV Neutrinos. BRAZILIAN JOURNAL OF PHYSICS, 51(5), 1406-1415.
    DOI
    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.
    DOI Scopus9 Europe PMC5
    2021 McCradden, M. D., & Chad, L. (2021). Screening for facial differences worldwide: equity and ethics. The Lancet Digital Health, 3(10), e615-e616.
    DOI Scopus1 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.
    DOI Scopus101 Europe PMC68
    2021 McCradden, M. D. (2021). When is accuracy off-target?. Translational Psychiatry, 11(1), 369.
    DOI Scopus7 Europe PMC3
    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.
    DOI Scopus2 Europe PMC1
    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.
    DOI
    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.
    DOI Scopus6 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.
    DOI Scopus64 Europe PMC31
    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.
    DOI Scopus51 Europe PMC32
    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), 9 pages.
    DOI Scopus42 Europe PMC23
    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.
    DOI Scopus7 Europe PMC3
    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.
    DOI Scopus44 Europe PMC16
    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.
    DOI Scopus137 Europe PMC74
    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.
    DOI Scopus11
    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.
    DOI Scopus301 Europe PMC152
    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.
    DOI Scopus196 Europe PMC91
    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.
    DOI Scopus179 Europe PMC90
    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.
    DOI WoS40 Europe PMC89
    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.
    DOI WoS53 Europe PMC121
    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.
    DOI Scopus444 Europe PMC230
    2019 Dey, R. K., Dam, S., & Basak, A. (2019). A novel approach for deducing the mass composition of cosmic rays from lateral densities of EAS particles. EPL, 127(3), 7 pages.
    DOI
    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.
    DOI Scopus90 Europe PMC52
    2019 McCradden, M. D., & Anderson, J. A. (2019). The Last Refuge of Privacy. AJOB Neuroscience, 10(1), 25-28.
    DOI
    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.
    DOI Scopus12 Europe PMC4
    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.
    DOI Scopus6 Europe PMC1
    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.
    DOI Scopus14
    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.
    DOI Scopus1 Europe PMC1
    2018 McCradden, M. D., & Cusimano, M. D. (2018). Questioning Assumptions About Vulnerability in Psychiatric Patients. AJOB Neuroscience, 9(4), 221-223.
    DOI
    - Behera, A., Saxena, K., Prakash, C., Pramanik, A., Haider, J., Basak, A., & Shankar, S. (n.d.). MODELING AND SIMULATION OF MAGNETRON-SPUTTERRED NiTi THIN FILM DEPOSITION BY SRIM/TRIM. SURFACE REVIEW AND LETTERS, 19 pages.
    DOI

  • Conference Papers
    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 Scopus12
    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
    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
    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.
    Scopus249
    2018 van Zijl, M. D., Koullali, B., Mol, B. W. J., Kazemier, B. M., & Pajkrt, E. (2018). How to measure the cervical length: A prospective cohort study in the Netherlands. In AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY Vol. 218 (pp. S263-S264). TX, Dallas: MOSBY-ELSEVIER.
    DOI
    2016 Cook, J., MacIntyre, D., Sykes, L., Bennett, P., & Terzidou, V. (2016). Expression of specific cell-free plasma microRNAs is associated with cervical shortening in women at risk of preterm birth. In BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY Vol. 123 (pp. 103). WILEY-BLACKWELL.

  • Report for External Bodies
    Year Citation
    2024 Semmler, C., Palmer, L., McCradden, M., Oakden-Rayner, L., & Tikhomirov, L. (2024). Submission to Senate Select Committee on Adopting Artificial Intelligence (AI) - Submission 95 (95).

  • Preprint
    Year Citation
    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.
    DOI

The Hospital Research Foundation Group Fellowship Grant

Centre for Augmented Reasoning, Australian Institute for Machine Learning

Canadian Institutes for Health Research

  • Memberships
    Date Role Membership Country
    2025 - ongoing Member Sigma Xi Scientific Research Honor Society United States
  • Position: THRF Clinical Research Fellow
  • Phone: 83133909
  • Email: melissa.mccradden@adelaide.edu.au
  • Campus: Lot 14
  • Building: Australian Institute for Machine Learning Building, floor Second Floor
  • Room: 2.21
  • Org Unit: Australian Institute for Machine Learning - Projects
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