The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Understanding artificial intelligence based radiology studies: What is overfitting?
Open accessAbstract
Artificial intelligence (AI) is a broad umbrella term used to encompass a wide variety of subfields dedicated to creating algorithms to perform tasks that mimic human intelligence. As AI development grows closer to clinical integration, radiologists will need to become familiar with the principles of artificial intelligence to properly evaluate and use this powerful tool. This series aims to explain certain basic concepts of artificial intelligence, and their applications in medical imaging starting with a concept of overfitting.
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“Overfitting is a common problem encountered during the validation of the model which may significantly impact its generalizability and contribute to bias among underrepresented groups of patients [42,43].”
From Bias in artificial intelligence algorithms and recommendations for mitigation (2023) · cites this paper as [42]
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The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
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Bias in artificial intelligence algorithms and recommendations for mitigation
Nazer, L. H., Zatarah, R., Waldrip, S., Ke, J. X. C., Moukheiber, M., Khanna, A. K., Hicklen, R. S., Moukheiber, L., Moukheiber, D., Ma, H., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000278 · Cited by 621
Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine
Ahn, J. S., Shin, S., Yang, S., Park, E. K., Kim, K. H., Cho, S. I., Ock, C., & Kim, S. (2023) · Journal of Breast Cancer · doi:10.4048/jbc.2023.26.e45 · Cited by 281
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ARTIFICIAL INTELLIGENCE IN BUSINESS AND ECONOMICS RESEARCH: TRENDS AND FUTURE
Ruiz–Real, J. L., Uribe-Toril, J., Torres, J. A., & Valenciano, J. D. P. (2020) · Journal of Business Economics and Management · doi:10.3846/jbem.2020.13641 · Cited by 223
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Metadata
- Authors
- Mutasa, S., Sun, S., & Ha, R.
- Affiliations
- NewYork–Presbyterian Hospital (US)
- Corresponding author
- Mutasa, Simukayi
- Sun, Shawn
- Ha, Richard
- Venue
- Clinical Imaging
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 65
- Pages
- 96-99
- ISSN
- 0899-7071 (ISSN-L)
- PMC
- PMC8150901
- OpenAlex
- W3020614853
- Cited by
- 216
- References
- 41
- Citations by year
- 2026: 14 · 2025: 30 · 2024: 41 · 2023: 61 · 2022: 32 · 2021: 26 · 2020: 12
- FWCI
- 2.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Imaging (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (R38CA231577)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- overfitting, artificial intelligence, machine learning, diagnostic imaging, radiology, deep learning, clinical implementation of AI
- MeSH terms
- Radiologists, Algorithms, Artificial Intelligence, Humans, Radiology
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