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Article

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer.

BMC cancer - 21 Sept 2022

Rączkowska Alicja, Paśnik Iwona, Kukiełka Michał, Nicoś Marcin, Budzinska Magdalena A, Kucharczyk Tomasz, Szumiło Justyna, Krawczyk Paweł, Crosetto Nicola, Szczurek Ewa

Abstract excerpt

BACKGROUND: Despite the fact that tumor microenvironment (TME) and gene mutations are the main determinants of progression of the deadliest cancer in the world - lung cancer, their interrelations are not well understood. Digital pathology data provides a unique insight into the spatial composition of the TME. Various spatial metrics and machine learning approaches were proposed for prediction of either patient...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 36131239
DOI: 10.1186/s12885-022-10081-w
PMCID: PMC9490924

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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