Explainable vs. interpretable artificial intelligence frameworks in oncology
- PMID: 36915595
- PMCID: PMC10007880
- DOI: 10.21037/tcr-22-2427
Explainable vs. interpretable artificial intelligence frameworks in oncology
Keywords: Explainable artificial intelligence (XAI); interpretable artificial intelligence; oncology.
Conflict of interest statement
Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-22-2427/coif). The authors have no conflicts of interest to declare.
Comment on
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Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review.Transl Cancer Res. 2022 Oct;11(10):3853-3868. doi: 10.21037/tcr-22-1626. Transl Cancer Res. 2022. PMID: 36388027 Free PMC article. Review.
References
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- Ribeiro MT, Singh S, Guestrin C, editors. "Why should i trust you?" Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining; 2016.
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- Lundberg SM, Lee SI. A unified approach to interpreting model predictions. NIPS'17: Proceedings of the 31st International Conference on Neural Information Processing Systems 2017;30:4768-77.
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