Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records

Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records

Abstract Background A new learning-based patient similarity measurement was proposed to measure patients’ similarity for heterogeneous electronic medical records (EMRs) data. Methods We first calculated feature-level similarities according to the features’ attributes. A domain expert provided patien...

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Bibliographic Details
Main Authors: Ni Wang, Yanqun Huang, Honglei Liu, Zhiqiang Zhang, Lan Wei, Xiaolu Fei, Hui Chen
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Patient similarity
Electronic medical records
Semi-supervised learning
k-nearest neighbors
Liver diseases
Online Access:https://doi.org/10.1186/s12911-021-01432-x

Internet

https://doi.org/10.1186/s12911-021-01432-x

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