The DOI matches its Crossref record; 146 of the 146 references it cites were found in a registry or an index.
Deep Learning in Biomedical Data Science
Abstract
Since the 1980s, deep learning and biomedical data have been coevolving and feeding each other. The breadth, complexity, and rapidly expanding size of biomedical data have stimulated the development of novel deep learning methods, and application of these methods to biomedical data have led to scientific discoveries and practical solutions. This overview provides technical and historical pointers to the field, and surveys current applications of deep learning to biomedical data organized around five subareas, roughly of increasing spatial scale: chemoinformatics, proteomics, genomics and transcriptomics, biomedical imaging, and health care. The black box problem of deep learning methods is also briefly discussed.
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“Baldi [135] explains this argument using examples of the lack of explainability of many processes in our daily lives, for example, how cars, computers, cell phones, or even our brains work.”
From Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review (2021) · cites this paper as [135]
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“On the other hand, there are some studies supporting that XAI is not always necessary [46,134,135].”
From Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review (2021) · cites this paper as [135]
Citations
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Cited by
Sorted by citations
Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning
Shao, S., McAleer, S., Yan, R., & Baldi, P. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2864759 · Cited by 1,690
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Antoniadi, A. M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B. A., & Mooney, C. (2021) · Applied Sciences · doi:10.3390/app11115088 · Cited by 629
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Metadata
- Authors
- Baldi, P.
- Affiliations
- University of California, Irvine (US)
- Corresponding author
- Baldi, Pierre
- ORCID
- Baldi, Pierre
- Venue
- Annual Review of Biomedical Data Science
- Publisher
- Annual Reviews
- Published
- 2018-07-20
- Volume
- 1
- Issue
- 1
- Pages
- 181-205
- ISSN
- 2574-3414 (ISSN-L)
- OpenAlex
- W2799441468
- Cited by
- 119
- References
- 143
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 17 · 2023: 17 · 2022: 18 · 2021: 15 · 2020: 16 · 2019: 12 · 2018: 7
- FWCI
- 1.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Biomedical Data Science (publishedVersion)
- Funders
- National Institutes of Health
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- deep learning, biomedical data, cheminformatics, proteomics, genomics, transcriptomics, biomedical imaging, health care, black box problem, history of deep learning
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