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

Artificial Intelligence (1740) Clinical Informatics (1162) Clinical Information and Decision Making (1656) Imaging Informatics (235) Machine Learning (1738) Advanced Data Analytics in eHealth (167)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44119, first published .
Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets

Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets

Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets

Authors of this article:

Chaoyue Chen1 Author Orcid Image ;   Yuen Teng1 Author Orcid Image ;   Shuo Tan2 Author Orcid Image ;   Zizhou Wang2, 3 Author Orcid Image ;   Lei Zhang2 Author Orcid Image ;   Jianguo Xu1 Author Orcid Image
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New in JMIR: Performance Test of a Well-Trained Model for Meningioma Segmentation in #HealthCare Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets https://t.co/wCVUARy3Fq

3:50 PM · Dec 15, 2023

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RT @jmirpub: New in JMIR: Performance Test of a Well-Trained Model for Meningioma Segmentation in #HealthCare Centers: Secondary Analysis B…

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Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets https://t.co/20DqMunGoy https://t.co/SDY83URNtc

5:21 PM · Dec 15, 2023

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Performance Test of a Well-Trained Model for #meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets https://t.co/SucAL37zQC

6:22 PM · Dec 15, 2023

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