Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future.
artificial intelligence
deep learning
lung cancer
Journal
Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402
Informations de publication
Date de publication:
31 Oct 2022
31 Oct 2022
Historique:
received:
28
09
2022
revised:
26
10
2022
accepted:
29
10
2022
entrez:
11
11
2022
pubmed:
12
11
2022
medline:
12
11
2022
Statut:
epublish
Résumé
Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays an essential role in each phase of lung cancer management, from detection to assessment of response to treatment. The development of imaging-based artificial intelligence (AI) models has the potential to play a key role in early detection and customized treatment planning. Computer-aided detection of lung nodules in screening programs has revolutionized the early detection of the disease. Moreover, the possibility to use AI approaches to identify patients at risk of developing lung cancer during their life can help a more targeted screening program. The combination of imaging features and clinical and laboratory data through AI models is giving promising results in the prediction of patients' outcomes, response to specific therapies, and risk for toxic reaction development. In this review, we provide an overview of the main imaging AI-based tools in lung cancer imaging, including automated lesion detection, characterization, segmentation, prediction of outcome, and treatment response to provide radiologists and clinicians with the foundation for these applications in a clinical scenario.
Identifiants
pubmed: 36359485
pii: diagnostics12112644
doi: 10.3390/diagnostics12112644
pmc: PMC9689810
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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