Artificial Intelligence in ALK-Rearranged NSCLC: Forecasting Response and Resistance

20260 citationsJournal Articlegold Open Access

Authors

Andreas Koulouris · Karolinska University Hospital

Christos Tsagkaris · Aristotle University of Thessaloniki

Konstantinos Kalaitzidis · Stockholm University

Georgios Tsakonas · Karolinska University Hospital

Giannis Mountzios · Henry Dunant Hospital

Abstract

AI shows promising potential to support diagnosis, prognostication, and treatment assessment in <i>ALK</i>-rearranged lung cancer. However, methodological heterogeneity, limited external validation, and a lack of prospective studies currently constrain clinical translation.

Topics & Keywords

Radiomics and Machine Learning in Medical Imaging Lung Cancer Diagnosis and Treatment Lung Cancer Research Studies

UN Sustainable Development Goals

Reduced inequalities

Publication Details

Published in: Cancers

Volume 18, Issue 6, pp. 973-973

DOI: 10.3390/cancers18060973

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