Work

Semi-supervised encoding for outlier detection in clinical observation data

Year: 2019

Type: article

Source: Computer Methods and Programs in Biomedicine

DOI: 10.1016/j.cmpb.2019.01.002

Authors: Hossein Estiri, Shawn N. Murphy

Institutions: Harvard University, Massachusetts General Hospital

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Patient-Centered Outcomes Research Institute, National Institutes of Health, National Human Genome Research Institute, U.S. National Library of Medicine

Awards: G1393766945, G560201083, G9000036806, G9000220833, G947657586

OpenAlex ID: W2949688312

FWCI: 1.727

Cites: 51

Cited by: 29

Related to: 10