Figures
Better medicine through machine learning: What's real, and what’s artificial?
In 2018, PLOS Medicine enlisted the expert guidance of Guest Editors Suchi Saria, Atul Butte, and Aziz Sheikh to establish the journal's scope and standards for publishing machine learning research in medicine. The tangible result can be seen in our articles within the PLOS Collection Machine Learning in Health Biomedicine, which continues to expand as our sister journals publish related research.
Going forward, PLOS Medicine is committed to providing our general medical readership with comprehensive, rigorous coverage of machine learning-related developments, with further expert commentary, in order to support clinicians as they learn how to understand, develop and ultimately leverage machine learning to improve patient care.
In this month's Editorial, Saria, Butte, and Sheikh finish our year—but not our shared journey!—with an accessible and accurate portrayal of the current forefront of machine learning in clinical translation.
Image Credit: geralt, Pixabay
Citation: (2018) PLoS Medicine Issue Image | Vol. 15(12) December 2018. PLoS Med 15(12): ev15.i12. https://doi.org/10.1371/image.pmed.v15.i12
Published: December 31, 2018
Copyright: © 2018 geralt. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In 2018, PLOS Medicine enlisted the expert guidance of Guest Editors Suchi Saria, Atul Butte, and Aziz Sheikh to establish the journal's scope and standards for publishing machine learning research in medicine. The tangible result can be seen in our articles within the PLOS Collection Machine Learning in Health Biomedicine, which continues to expand as our sister journals publish related research.
Going forward, PLOS Medicine is committed to providing our general medical readership with comprehensive, rigorous coverage of machine learning-related developments, with further expert commentary, in order to support clinicians as they learn how to understand, develop and ultimately leverage machine learning to improve patient care.
In this month's Editorial, Saria, Butte, and Sheikh finish our year—but not our shared journey!—with an accessible and accurate portrayal of the current forefront of machine learning in clinical translation.
Image Credit: geralt, Pixabay