Work

Harnessing machine learning to the immuohistochemical expression of AMBRA1 and Loricin to identify non-ulcerated AJCC Stage I/II melanomas at high-risk of metastasis

Year: 2025

Type: article

Abstract: Background: Precision-based personalised biomarkers able to identify both low-risk and high-risk patient subpopulations with localised cutaneous melanoma are urgently needed to guide clinical follow up and treatment stratification.

Source: EJC Skin Cancer

DOI: 10.1016/j.ejcskn.2025.100493

Authors: P. Lovat, S. Grant, T. Andrew, G. Paragh, P. Sloan, M. Labus, J. Armstrong

Institutions: Newcastle University, Roswell Park Comprehensive Cancer Center, University of Sunderland

Language: English

Topic: Cutaneous Melanoma Detection and Management

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,340

OpenAlex ID: W4409145475

FWCI:

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