{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T04:21:53Z","timestamp":1765254113739,"version":"build-2065373602"},"reference-count":72,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,31]],"date-time":"2020-12-31T00:00:00Z","timestamp":1609372800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Lung cancer is still the leading cause of cancer death in the world. For this reason, novel approaches for early and more accurate diagnosis are needed. Computer-aided decision (CAD) can be an interesting option for a noninvasive tumour characterisation based on thoracic computed tomography (CT) image analysis. Until now, radiomics have been focused on tumour features analysis, and have not considered the information on other lung structures that can have relevant features for tumour genotype classification, especially for epidermal growth factor receptor (EGFR), which is the mutation with the most successful targeted therapies. With this perspective paper, we aim to explore a comprehensive analysis of the need to combine the information from tumours with other lung structures for the next generation of CADs, which could create a high impact on targeted therapies and personalised medicine. The forthcoming artificial intelligence (AI)-based approaches for lung cancer assessment should be able to make a holistic analysis, capturing information from pathological processes involved in cancer development. The powerful and interpretable AI models allow us to identify novel biomarkers of cancer development, contributing to new insights about the pathological processes, and making a more accurate diagnosis to help in the treatment plan selection.<\/jats:p>","DOI":"10.3390\/jcm10010118","type":"journal-article","created":{"date-parts":[[2020,12,31]],"date-time":"2020-12-31T10:10:37Z","timestamp":1609409437000},"page":"118","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Comprehensive Perspective for Lung Cancer Characterisation Based on AI Solutions Using CT Images"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1681-2436","authenticated-orcid":false,"given":"Tania","family":"Pereira","sequence":"first","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, INESC TEC, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7162-414X","authenticated-orcid":false,"given":"Cl\u00e1udia","family":"Freitas","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, FMUP, 4200-319 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7132-4094","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"Costa","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Porto, FMUP, 4200-319 Porto, Portugal"},{"name":"Institute for Research and Innovation in Health of the University of Porto, i3S, 4200-135 Porto, Portugal"},{"name":"Institute of Molecular Pathology and Immunology of the University of Porto, IPATIMUP, 4200-135 Porto, Portugal"}]},{"given":"Joana","family":"Morgado","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, INESC TEC, 4200-465 Porto, Portugal"},{"name":"Faculty of Science, University of Porto, FCUP, 4169-007 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3069-2282","authenticated-orcid":false,"given":"Francisco","family":"Silva","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, INESC TEC, 4200-465 Porto, Portugal"}]},{"given":"Eduardo","family":"Negr\u00e3o","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"}]},{"given":"Beatriz Flor","family":"de Lima","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"}]},{"given":"Miguel Correia","family":"da Silva","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"}]},{"given":"Ant\u00f3nio J.","family":"Madureira","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"}]},{"given":"Isabel","family":"Ramos","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, FMUP, 4200-319 Porto, Portugal"}]},{"given":"Venceslau","family":"Hespanhol","sequence":"additional","affiliation":[{"name":"Centro Hospitalar e Universit\u00e1rio de S\u00e3o Jo\u00e3o, CHUSJ, 4200-319 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, FMUP, 4200-319 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3458-7693","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Cunha","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, INESC TEC, 4200-465 Porto, Portugal"},{"name":"Department of Engineering, University of Tr\u00e1s-os-Montes and Alto Douro, UTAD, 5001-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6193-8540","authenticated-orcid":false,"given":"H\u00e9lder P.","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, INESC TEC, 4200-465 Porto, Portugal"},{"name":"Faculty of Science, University of Porto, FCUP, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1186\/s13045-019-0783-9","article-title":"Incidence and death in 29 cancer groups in 2017 and trend analysis from 1990 to 2017 from the Global Burden of Disease Study","volume":"12","author":"Lin","year":"2019","journal-title":"J. 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