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Using unsupervised learning to determine risk level for left ventricular diastolic dysfunction

Year: 2014

Type: conference-paper

Source: IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

DOI: 10.1109/bibm.2014.6999182

Authors: Kaidi Ma, Marco Canepa, James B. Strait, Hagit Shatkay

Institutions: University of Delaware, National Institutes of Health, National Institute on Aging

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W2062285448

FWCI:

Cites: 20

Cited by: 2

Related to: 10