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Article

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Scientific reports - 16 Aug 2021

Sadhwani Apaar, Chang Huang-Wei, Behrooz Ali, Brown Trissia, Auvigne-Flament Isabelle, Patel Hardik, Findlater Robert, Velez Vanessa, Tan Fraser, Tekiela Kamilla, Wulczyn Ellery, Yi Eunhee S, Mermel Craig H, Hanks Debra, Chen Po-Hsuan Cameron, Kulig Kimary, Batenchuk Cory, Steiner David F, Cimermancic Peter

Abstract excerpt

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires use of finite tissue specimens and costly, time-consuming laboratory processes. Histologic subtype classification represents an established component of lung...

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Identifiers

PMID: 34400666
DOI: 10.1038/s41598-021-95747-4
PMCID: PMC8368039

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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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