The Clinician and Dataset Shift in Artificial Intelligence

This letter outlines how to identify, and potentially mitigate, common sources of “dataset shift” in machine-learning systems. This occurs when the model “training data” differ from the data used by the model to provide diagnostic, prognostic, or treatment advice.

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Bibliographic Details
Published in:	The New England journal of medicine Vol. 385; no. 3; pp. 283 - 286
Main Authors:	Finlayson, Samuel G, Subbaswamy, Adarsh, Singh, Karandeep, Bowers, John, Kupke, Annabel, Zittrain, Jonathan, Kohane, Isaac S, Saria, Suchi
Format:	Journal Article
Language:	English
Published:	United States Massachusetts Medical Society 15.07.2021
Subjects:	Accuracy Algorithms and Education Artificial Intelligence Calibration Clinical medicine Clinical Practice Clinical trials COVID-19 Datasets Datasets as Topic Demographics Health IT Health Policy Hospitalist Hospitals Humans Influenza Information Technology Learning algorithms Machine Learning Medical Informatics Medical Practice Patients Primary Care Quality of Care Reimbursement Sepsis Software Training Trends
ISSN:	0028-4793, 1533-4406, 1533-4406
Online Access:	Get full text
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