This paper is in the following e-collection/theme issue:

Tools, Programs and Algorithms (266) Data Science (270) Articles* (13) Big Data (240)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38590, first published .
Dealing With Missing, Imbalanced, and Sparse Features During the Development of a Prediction Model for Sudden Death Using Emergency Medicine Data: Machine Learning Approach

Dealing With Missing, Imbalanced, and Sparse Features During the Development of a Prediction Model for Sudden Death Using Emergency Medicine Data: Machine Learning Approach

Dealing With Missing, Imbalanced, and Sparse Features During the Development of a Prediction Model for Sudden Death Using Emergency Medicine Data: Machine Learning Approach

Authors of this article:

Xiaojie Chen1 Author Orcid Image ;   Han Chen2 Author Orcid Image ;   Shan Nan1 Author Orcid Image ;   Xiangtian Kong3 Author Orcid Image ;   Huilong Duan1, 4 Author Orcid Image ;   Haiyan Zhu2, 5 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

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