Melissa D. McCradden

7.6k total citations
48 papers, 1.0k citations indexed

About

Melissa D. McCradden is a scholar working on Health Informatics, Public Health, Environmental and Occupational Health and General Health Professions. According to data from OpenAlex, Melissa D. McCradden has authored 48 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Health Informatics, 17 papers in Public Health, Environmental and Occupational Health and 11 papers in General Health Professions. Recurrent topics in Melissa D. McCradden's work include Artificial Intelligence in Healthcare and Education (33 papers), Ethics in Clinical Research (13 papers) and Explainable Artificial Intelligence (XAI) (8 papers). Melissa D. McCradden is often cited by papers focused on Artificial Intelligence in Healthcare and Education (33 papers), Ethics in Clinical Research (13 papers) and Explainable Artificial Intelligence (XAI) (8 papers). Melissa D. McCradden collaborates with scholars based in Canada, United States and United Kingdom. Melissa D. McCradden's co-authors include Shalmali Joshi, James A. Anderson, Mjaye Mazwi, Daniel Z. Buchman, Anna Goldenberg, James A. Anderson, Michael D. Cusimano, Elizabeth A. Stephenson, Ben Glocker and Lauren Oakden‐Rayner and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and Journal of neurosurgery.

In The Last Decade

Melissa D. McCradden

43 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Melissa D. McCradden Canada 16 506 276 276 221 121 48 1.0k
Irene Y. Chen United States 9 480 0.9× 384 1.4× 112 0.4× 251 1.1× 104 0.9× 30 1.0k
Danton Char United States 13 771 1.5× 382 1.4× 275 1.0× 368 1.7× 126 1.0× 45 1.6k
Adam Poliak United States 11 818 1.6× 607 2.2× 169 0.6× 303 1.4× 224 1.9× 24 1.6k
Atheer Aldairem Saudi Arabia 3 617 1.2× 294 1.1× 137 0.5× 271 1.2× 92 0.8× 6 1.2k
Sumaya N. Almohareb Saudi Arabia 4 617 1.2× 294 1.1× 137 0.5× 271 1.2× 92 0.8× 15 1.3k
Irene Dankwa‐Mullan United States 17 301 0.6× 215 0.8× 259 0.9× 183 0.8× 281 2.3× 60 1.1k
David Chartash United States 8 1.1k 2.2× 420 1.5× 169 0.6× 549 2.5× 103 0.9× 25 1.4k
Tirth Dave Ukraine 7 739 1.5× 292 1.1× 99 0.4× 317 1.4× 105 0.9× 43 1.1k
Himel Mondal India 18 663 1.3× 307 1.1× 148 0.5× 348 1.6× 137 1.1× 197 1.4k
Sonoo Thadaney-Israni United States 5 304 0.6× 228 0.8× 113 0.4× 128 0.6× 59 0.5× 6 640

Countries citing papers authored by Melissa D. McCradden

Since Specialization
Citations

This map shows the geographic impact of Melissa D. McCradden's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Melissa D. McCradden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Melissa D. McCradden more than expected).

Fields of papers citing papers by Melissa D. McCradden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Melissa D. McCradden. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Melissa D. McCradden. The network helps show where Melissa D. McCradden may publish in the future.

Co-authorship network of co-authors of Melissa D. McCradden

This figure shows the co-authorship network connecting the top 25 collaborators of Melissa D. McCradden. A scholar is included among the top collaborators of Melissa D. McCradden based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Melissa D. McCradden. Melissa D. McCradden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pinto, Andrew D., Shehzad Ali, David L. Buckeridge, et al.. (2025). Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation. JMIR Public Health and Surveillance. 11. e68952–e68952.
2.
Ziegler, Carolyn, Shehzad Ali, David L. Buckeridge, et al.. (2025). Machine learning used to study risk factors for chronic diseases: A scoping review. Canadian Journal of Public Health. 117(1). 125–139. 1 indexed citations
3.
McCradden, Melissa D., et al.. (2025). What makes a ‘good’ decision with artificial intelligence? A grounded theory study in paediatric care. BMJ evidence-based medicine. 30(3). 183–193. 1 indexed citations
4.
McCradden, Melissa D., et al.. (2024). Explaining decisions without explainability? Artificial intelligence and medicolegal accountability. SHILAP Revista de lepidopterología. 11(3). 100171–100171. 5 indexed citations
5.
Semmler, Carolyn, et al.. (2024). Medical artificial intelligence for clinicians: the lost cognitive perspective. The Lancet Digital Health. 6(8). e589–e594. 16 indexed citations
6.
Alderman, Joseph, Elinor Laws, Joanne Palmer, et al.. (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. 3 indexed citations
7.
Katzman, Debra K. & Melissa D. McCradden. (2023). Capacity for Preferences: Adolescents With AN-PLUS. Journal of Adolescent Health. 72(6). 827–828. 2 indexed citations
8.
Gonorazky, Hernán, et al.. (2023). Understanding caregiver experiences with disease-modifying therapies for spinal muscular atrophy: a qualitative study. Archives of Disease in Childhood. 108(11). 929–934. 5 indexed citations
9.
10.
Bradshaw, Tyler, Melissa D. McCradden, Abhinav K. Jha, et al.. (2023). Artificial Intelligence Algorithms Need to Be Explainable—or Do They?. Journal of Nuclear Medicine. 64(6). 976–977. 10 indexed citations
11.
Wagner, Matthias, Asthik Biswas, Farzad Khalvati, et al.. (2022). Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence. Pediatric Radiology. 52(11). 2111–2119. 7 indexed citations
12.
Kwong, Jethro C.C., Lauren Erdman, Adree Khondker, et al.. (2022). The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers in Digital Health. 4. 929508–929508. 26 indexed citations
13.
Laussen, Peter C., Andrew Goodwin, Sebastian D. Goodfellow, et al.. (2022). An integration engineering framework for machine learning in healthcare. Frontiers in Digital Health. 4. 932411–932411. 10 indexed citations
14.
Liu, Xiaoxuan, Ben Glocker, Melissa D. McCradden, et al.. (2022). The medical algorithmic audit. The Lancet Digital Health. 4(5). e384–e397. 121 indexed citations
15.
McCradden, Melissa D., et al.. (2020). Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research. BMJ Open. 10(10). e039798–e039798. 51 indexed citations
16.
McCradden, Melissa D., Shalmali Joshi, Mjaye Mazwi, & James A. Anderson. (2020). Ethical limitations of algorithmic fairness solutions in health care machine learning. The Lancet Digital Health. 2(5). e221–e223. 137 indexed citations
17.
McCradden, Melissa D., Denitsa Vasileva, Ani Orchanian‐Cheff, & Daniel Z. Buchman. (2019). Ambiguous identities of drugs and people: A scoping review of opioid-related stigma. International Journal of Drug Policy. 74. 205–215. 83 indexed citations
18.
Tonekaboni, Sana, Shalmali Joshi, Melissa D. McCradden, & Anna Goldenberg. (2019). What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.. 359–380. 9 indexed citations
19.
McCradden, Melissa D. & Michael D. Cusimano. (2018). Concussions in Sledding Sports and the Unrecognized “Sled Head”: A Systematic Review. Frontiers in Neurology. 9. 772–772. 12 indexed citations
20.
McCradden, Melissa D. & Michael D. Cusimano. (2018). Questioning Assumptions About Vulnerability in Psychiatric Patients. AJOB Neuroscience. 9(4). 221–223. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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