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Satellite images and machine learning can identify remote communities to facilitate access to health services.

08:00 EDT 14th August 2019 | BioPortfolio

Summary of "Satellite images and machine learning can identify remote communities to facilitate access to health services."

Community health systems operating in remote areas require accurate information about where people live to efficiently provide services across large regions. We sought to determine whether a machine learning analyses of satellite imagery can be used to map remote communities to facilitate service delivery and planning.

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This article was published in the following journal.

Name: Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
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Medical and Biotech [MESH] Definitions

Composition of images of EARTH or other planets from data collected during SPACE FLIGHT by remote sensing instruments onboard SPACECRAFT. The satellite sensor systems measure and record absorbed, emitted, or reflected energy across the spectra, as well as global position and time.

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.

SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.

A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.

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