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. 2022 Feb 17;12:773840. doi: 10.3389/fonc.2022.773840

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Copyright © 2022 Zhang, Zhang, Zhang, Qiu, Tan, Yin and Liao

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Conceptually, radiomics and deep learning in radiology allow the application of three essential types of image-based clinical tasks: 1) Detection of regions of interest, including cancerous, non-cancerous, and normal tissue; 2) Segmentation of target regions, disease diagnosis, and patient stratification; 3) Treatment response or prognosis and tissue progression. TNM, tumor node metastasis; EGFR, epidermal growth factor receptor; SCLC, small cell lung cancer; LNM, lymph node metastasis; NAC, neoadjuvant chemotherapy.