3D deep learning model to predict the recurrence of stage IA invasive lung adenocarcinoma after sub-lobar resection: a multicenter retrospective cohort study.

Fan X, Liang C, Ma XQ, Feng YB, Fan QR, Wang DW, Luo TY, Lv FJ, Li Q

Open source

DOI
10.1007/s10278-026-01925-z
Published
2026 Mar 31
Container
Journal of imaging informatics in medicine
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1007/s10278-026-01925-z,
  title = {3D deep learning model to predict the recurrence of stage IA invasive lung adenocarcinoma after sub-lobar resection: a multicenter retrospective cohort study.},
  author = {Fan X and Liang C and Ma XQ and Feng YB and Fan QR and Wang DW and Luo TY and Lv FJ and Li Q},
  year = {2026},
  journal = {Journal of imaging informatics in medicine},
  doi = {10.1007/s10278-026-01925-z},
  url = {https://doi.org/10.1007/s10278-026-01925-z}
}

RIS

TY  - JOUR
TI  - 3D deep learning model to predict the recurrence of stage IA invasive lung adenocarcinoma after sub-lobar resection: a multicenter retrospective cohort study.
AU  - Fan X
AU  - Liang C
AU  - Ma XQ
AU  - Feng YB
AU  - Fan QR
AU  - Wang DW
AU  - Luo TY
AU  - Lv FJ
AU  - Li Q
PY  - 2026
JO  - Journal of imaging informatics in medicine
DO  - 10.1007/s10278-026-01925-z
UR  - https://doi.org/10.1007/s10278-026-01925-z
ER  - 

APA

X, F., C, L., XQ, M., YB, F., QR, F., DW, W., TY, L., FJ, L., & Q, L. (2026). 3D deep learning model to predict the recurrence of stage IA invasive lung adenocarcinoma after sub-lobar resection: a multicenter retrospective cohort study.. Journal of imaging informatics in medicine. https://doi.org/10.1007/s10278-026-01925-z

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