Health AI Central
Peer-Reviewed Publication
J Thorac Dis2026;18(7):742.July 31, 2026Journal Article

Interpretable machine learning model integrating delta-radiomics enhances postoperative recurrence prediction in early-stage lung adenocarcinoma.

Feiyang Zhong1,2, Wenping Li3, Lijun Wu2, Qiaohui Lu3, Pengxin Yu4, Yuan Fang5, Shaohong Zhao1,2
1School of Medicine, Nankai University, Tianjin, China.
2Department of Radiology, The First Medical Center of the Chinese PLA General Hospital, Beijing, China.
3Department of Radiology, The Sixth Medical Center of the Chinese PLA General Hospital, Beijing, China.
4Institute of Advanced Research, Infervision Medical Technology Co., Ltd, Beijing, China.
5Department of Radiology, Air Force Medical Center, Air Force Medical University, PLA, Beijing, China.
PubMed PMC DOI PDF

Abstract

BACKGROUND: Despite curative resection for early-stage lung adenocarcinoma (LUAD), postoperative recurrence remains a significant concern, with substantial outcome heterogeneity even among patients with stage IA disease. An accurate tool to identify individuals at high risk of early postoperative recurrence after curative resection is urgently needed to guide intensified surveillance and adjuvant…

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