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Label-efficient computational tumour infiltrating lymphocyte assessment in breast cancer (ECTIL): multicentre validation in 2340 patients with breast cancer.

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Bibliographic Details
Title: Label-efficient computational tumour infiltrating lymphocyte assessment in breast cancer (ECTIL): multicentre validation in 2340 patients with breast cancer.
Authors: Schirris Y; Informatics Institute, University of Amsterdam, Amsterdam, Netherlands; Department of Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Voorthuis R; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Opdam M; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Liefaard M; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Sonke GS; Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands., Dackus G; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., de Jong V; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Wang Y; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Van Rossum A; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands., Steenbruggen TG; Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands., Steggink LC; Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, Netherlands., de Vries EGE; Department of Medical Oncology, University Medical Center Groningen, Groningen, Netherlands., van de Vijver M; Department of Pathology, The Amsterdam University Medical Centre, The University of Amsterdam, Amsterdam, Netherlands., Salgado R; Department of Pathology, ZAS Hospitals, Antwerp, Belgium; Division of Research, Peter MacCallum Centre, Melbourne, VIC, Australia., Gavves E; Informatics Institute, University of Amsterdam, Amsterdam, Netherlands., van Diest PJ; Division of Pathology, University Medical Center Utrecht, Utrecht, Netherlands., Linn SC; Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands; Division of Pathology, University Medical Center Utrecht, Utrecht, Netherlands., Teuwen J; Informatics Institute, University of Amsterdam, Amsterdam, Netherlands; AI for Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands., Menezes R; Biostatistics Centre, Department of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, Netherlands., Kok M; Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands; Department of Tumour Biology and Immunology, Netherlands Cancer Institute, Amsterdam, Netherlands., Horlings HM; Department of Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands. Electronic address: h.horlings@nki.nl.
Source: The Lancet. Digital health [Lancet Digit Health] 2025 Nov; Vol. 7 (11), pp. 100921. Date of Electronic Publication: 2025 Dec 10.
Publication Type: Journal Article; Multicenter Study; Validation Study
Journal Info: Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101751302 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2589-7500 (Electronic) Linking ISSN: 25897500 NLM ISO Abbreviation: Lancet Digit Health Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2589-7500
DOI:10.1016/j.landig.2025.100921