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

Statistical Methods for Surveillance and Population Health (188) Innovations and Technology for Cancer Prevention and Screening (201) Clinical Information and Decision Making (1915) Lung Cancer (66) Innovations in Cancer Diagnostic and Decision Support (109) Cancer Survivorship (334)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46737, first published .
Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study

Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study

Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study

Authors of this article:

Fan-Tsui Meng1, 2 Author Orcid Image ;   Jing-Rong Jhuang3 Author Orcid Image ;   Yan-Teng Peng2 Author Orcid Image ;   Chun-Ju Chiang1, 4 Author Orcid Image ;   Ya-Wen Yang1, 4 Author Orcid Image ;   Chi-Yen Huang5 Author Orcid Image ;   Kuo-Ping Huang5 Author Orcid Image ;   Wen-Chung Lee1, 4, 6 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Cui Y, Li X, Zhang H, Yuan W, Zhu E. MicroRNA‑199a‑3p suppresses non‑small cell lung cancer progression by targeting FTO to enhance m6A‑mediated downregulation of MZF1 and its transcriptional activation of CLDND1. Molecular Medicine Reports 2025;33(1):1 View