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When Leonard D'Avolio (Figure 1) was working on his Ph.D. degree in biomedical informatics, he saw the power of machine learning in transforming multiple industries; health care, however, was not among them. "The reason that Amazon, Netflix, and Google have transformed their industries is because they have embedded learning throughout every aspect of what they do. If we could prove that is possible in health care too, I thought we would have the potential to have a huge impact," he says.
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Name: IEEE pulse
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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.
Nurses whose work combines elements of both primary care nursing and public health practice and takes place primarily outside the therapeutic institution. Primary nursing care is directed to individuals, families, or groups in their natural settings within communities.