An online platform for interactive feedback in biomedical machine learning

被引：8

作者：

Abid, Abubakar ^{[1
,2
]}

Abdalla, Ali ^{[2
]}

Abid, Ali ^{[2
]}

Khan, Dawood ^{[2
]}

Alfozan, Abdulrahman ^{[2
]}

Zou, James ^{[1
,3
]}

机构：

[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA

[2] Gradio Labs, Mountain View, CA USA

[3] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA

来源：

NATURE MACHINE INTELLIGENCE | 2020年 / 2卷 / 02期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

D O I：

10.1038/s42256-020-0147-8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：86 / 88

页数：3

共 14 条

[1] A guide to deep learning in healthcare
Esteva, Andre
Robicquet, Alexandre
Ramsundar, Bharath
Kuleshov, Volodymyr
DePristo, Mark
Chou, Katherine
Cui, Claire
Corrado, Greg
Thrun, Sebastian
Dean, Jeff
[J]. NATURE MEDICINE, 2019, 25 (01) : 24 - 29
[2] Adversarial attacks on medical machine learning
Finlayson, Samuel G.
Bowers, John D.
Ito, Joichi
Zittrain, Jonathan L.
Beam, Andrew L.
Kohane, Isaac S.
[J]. SCIENCE, 2019, 363 (6433) : 1287 - 1289
[3] Ghorbani A., 2019, PREPRINT, DOI [10.1101/681676, DOI 10.1101/681676]
[4] Causability and explainability of artificial intelligence in medicine
Holzinger, Andreas
Langs, Georg
Denk, Helmut
Zatloukal, Kurt
Mueller, Heimo
[J]. WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2019, 9 (04)
[5] Interactive machine learning: experimental evidence for the human in the algorithmic loop: A case study on Ant Colony Optimization
Holzinger, Andreas
Plass, Markus
Kickmeier-Rust, Michael
Holzinger, Katharina
Crisan, Gloria Cerasela
Pintea, Camelia-M.
Palade, Vasile
[J]. APPLIED INTELLIGENCE, 2019, 49 (07) : 2401 - 2414
[6] Klemm S., 2018, PREPRINT
[7] New machine-learning technologies for computer-aided diagnosis
Lynch, Charles J.
Liston, Conor
[J]. NATURE MEDICINE, 2018, 24 (09) : 1304 - 1305
[8] DASH: Deep Learning for the Automated Spectral Classification of Supernovae and Their Hosts
Muthukrishna, Daniel
Parkinson, David
Tucker, Brad E.
[J]. ASTROPHYSICAL JOURNAL, 2019, 885 (01)
[9] Making Machine Learning Models Clinically Useful
Shah, Nigam H.
Milstein, Arnold
Bagley, Steven C.
[J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2019, 322 (14): : 1351 - 1352
[10] Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shen, Li
Margolies, Laurie R.
Rothstein, Joseph H.
Fluder, Eugene
McBride, Russell
Sieh, Weiva
[J]. SCIENTIFIC REPORTS, 2019, 9 (1)

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