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Medicine & Health

Machine Learning in Health and Biomedicine

Special Issues

Modern statistical modeling techniques—often called machine learning—are posited as a transformative force for human health. High-profile reports of diagnostic success demonstrate promise, but head-to-head comparisons to classical analyses of clinical data indicate that restraint is warranted. Practical questions are also timely. Will machine learning drive precision medicine? Will it elevate care in low-resource settings? How will the clinician interact with the machine? In this Collection, PLOS ONE, PLOS Computational Biology, PLOS Medicine and our teams of Guest Editors will feature research that applies machine learning methods to health and biomedicine. These articles will be accompanied by expert commentary on the application, impact, and ethics of these approaches.

Image Credit: StockSnap, Pixabay

Guest Editors (PLOS Medicine Special Issue)
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    Atul Butte
    Dr. Atul Butte
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    Suchi Saria
    Dr. Suchi Saria
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    Aziz Sheikh
    Dr. Aziz Sheikh
PLOS Medicine Special Issue
Collection Editor (PLOS Computational Biology)
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    Quaid Morris
    Dr. Quaid Morris
PLOS Computational Biology Collection
Guest Editors (PLOS ONE)
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    Leo Anthony Celi
    Dr. Leo Anthony Celi
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    LucaCiti
    Dr. Luca Citi
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    Marzyeh Ghassemi
    Dr. Marzyeh Ghassemi
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    Tom Pollard
    Dr. Tom Pollard
Collection Overview: PLOS ONE
PLOS ONE Collection: Acute Care
PLOS ONE Collection: Primary Care
PLOS ONE Collection: Mental Health
PLOS ONE Collection: Global Health
PLOS ONE Collection: Medical Imaging
PLOS ONE Collection: Ophthalmology
PLOS ONE Collection: Biobank and Omics Studies
PLOS ONE Collection: Miscellaneous
Machine Learning in Health and Biomedicine: A PLOS cross-journal Call for Papers 

Read the original Call For Papers on the Speaking of Medicine blog.

Click Here
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