Machine learning models have great potential in biomedical applications. A new platform called GradioHub offers an interactive and intuitive way for clinicians and biomedical researchers to try out models and test their reliability on real-world, out-of-training data.
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Users can interact with curated models on GradioHub at https://www.gradiohub.com. The code for the GradioHub Python library is available at https://github.com/gradio-app/gradio-UI, and an additional tutorial on creating interactive interfaces with GradioHub is provided at https://www.gradiohub.com/getting_started.html.
Lynch, C. J. & Liston, C. Nat. Med. 24, 1304–1305 (2018).
Wiens, J. et al. Nat. Med. 25, 1337–1340 (2019).
Esteva, A. et al. Nat Med. 25, 24–29 (2019).
Shah, N. H., Milstein, A. & Bagley, S. C. J. Am. Med. Assoc. 322, 1351–1352 (2019).
Nat. Biomed. Eng. 2, 709–710 (2018).
Zou, J. et al. Nat. Genet. 51, 12–18 (2019).
Zech, J. R. et al. PLOS Med. 15, e1002683 (2018).
Finlayson, S. G. et al. Science 363, 1287–1289 (2019).
Holzinger, A., Langs, G., Denk, H., Zatloukal, K. & Müller, H. WIRes Data Min. Knowl. Discov. 9, e1312 (2019).
Holzinger, A. et al. Appl. Intell. 49, 2401–2414 (2019).
Xu, K. et al. in Proc. 2018 CHI Conference on Human Factors in Computing Systems 663 (ACM, 2018).
Muthukrishna, D., Parkinson, D. & Tucker, B. E. Astrophys. J. 885, 85 (2019).
Klemm, S., Scherzinger, A., Drees, D. & Jiang, X. Preprint at https://arxiv.org/abs/1802.04626 (2018).
Ghorbani, A. et al. Preprint at https://doi.org/10.1101/681676 (2019).
Shen, L. et al. Sci. Rep. 9, 12495 (2019).
We would like to thank D. Ouyang, A. Ghorbani and A. Pampari for feedback. J.Z. is supported by the National Science Foundation grant CCF 1763191, and National Institutes of Health grants R21 MD012867-01 and P30AG059307, and grants from the Silicon Valley Foundation and the Chan Zuckerberg Initiative.
The first five authors are affiliated with Gradio Labs.
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Abid, A., Abdalla, A., Abid, A. et al. An online platform for interactive feedback in biomedical machine learning. Nat Mach Intell 2, 86–88 (2020). https://doi.org/10.1038/s42256-020-0147-8
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