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Editorial
. 2022 Jan 20;22(Suppl 12):443.
doi: 10.1186/s12859-021-04368-1.

The challenges of explainable AI in biomedical data science

Henry Han  1 , Xiangrong Liu  2
Affiliations
Editorial

The challenges of explainable AI in biomedical data science

Henry Han et al. BMC Bioinformatics. .
No abstract available

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Conflict of interest statement

The authors declare that they have no competing interests.

References

    1. Liu X, et al. Quantifying critical states of complex diseases using single-sample dynamic network biomarker. PLoS Comput Biol. 2017;13(7):e1005633. doi: 10.1371/journal.pcbi.1005633. - DOI - PMC - PubMed
    1. Han H. Diagnostic biases in translational bioinformatics. BMC Med Genomics. 2015;8:46. doi: 10.1186/s12920-015-0116-y. - DOI - PMC - PubMed
    1. Han H, Jiang X. Overcome support vector machine diagnosis overfitting. Cancer Inform. 2014;13(1):145–158. - PMC - PubMed
    1. Vilone G, Longo L. Explainable artificial intelligence: a systematic review. https://arxiv.org/abs/2006.00093 (2020)

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