Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC?

Kentaro Inamura; Yasuyuki Shigematsu

doi:10.21037/jtd-22-1862

Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC?

J Thorac Dis. 2023 May 30;15(5):2882-2884. doi: 10.21037/jtd-22-1862. Epub 2023 Apr 23.

Authors

Kentaro Inamura^{1

2}, Yasuyuki Shigematsu^{1

2}

Affiliations

¹ Division of Pathology, The Cancer Institute, Japanese Foundation for Cancer Research, Tokyo, Japan.
² Department of Pathology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.

No abstract available

Keywords: Artificial intelligence; digital pathology; immune checkpoint inhibitor (ICI); non-small cell lung cancer (NSCLC); tumor microenvironment.

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