Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective
- PMID: 36682439
- DOI: 10.1016/j.semcancer.2023.01.006
Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective
Abstract
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the world. The overall five-year survival rate of lung cancer is relatively lower than many leading cancers. Early diagnosis and prognosis of lung cancer are essential to improve the patient's survival rate. With artificial intelligence (AI) approaches widely applied in lung cancer, early diagnosis and prediction have achieved excellent performance in recent years. This review summarizes various types of AI algorithm applications in lung cancer, including natural language processing (NLP), machine learning and deep learning, and reinforcement learning. In addition, we provides evidence regarding the application of AI in lung cancer diagnostic and clinical prognosis. This review aims to elucidate the value of AI in lung cancer diagnosis and prognosis as the novel screening decision-making for the precise treatment of lung cancer patients.
Keywords: Artificial intelligence; Lung cancer diagnosis; Machine learning and deep learning; Natural language processing; Precision oncology.
Copyright © 2023 Elsevier Ltd. All rights reserved.
Conflict of interest statement
Declaration of Competing Interest None.
Similar articles
-
Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis.Clin Chem Lab Med. 2022 Jun 30;60(12):1974-1983. doi: 10.1515/cclm-2022-0291. Print 2022 Nov 25. Clin Chem Lab Med. 2022. PMID: 35771735 Review.
-
Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges.Cancer Lett. 2020 Feb 28;471:61-71. doi: 10.1016/j.canlet.2019.12.007. Epub 2019 Dec 10. Cancer Lett. 2020. PMID: 31830558 Review.
-
Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer.Curr Oncol. 2022 Mar 7;29(3):1773-1795. doi: 10.3390/curroncol29030146. Curr Oncol. 2022. PMID: 35323346 Free PMC article. Review.
-
Applications of artificial intelligence in urologic oncology.Investig Clin Urol. 2024 May;65(3):202-216. doi: 10.4111/icu.20230435. Investig Clin Urol. 2024. PMID: 38714511 Free PMC article. Review.
-
Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications.Diagn Interv Imaging. 2023 Jan;104(1):18-23. doi: 10.1016/j.diii.2022.10.004. Epub 2022 Oct 18. Diagn Interv Imaging. 2023. PMID: 36270953 Review.
Cited by
-
FANCA promotes lung adenocarcinoma progression and is a potential target for epitope vaccine immunotherapy.J Transl Med. 2024 Oct 7;22(1):911. doi: 10.1186/s12967-024-05675-w. J Transl Med. 2024. PMID: 39375712 Free PMC article.
-
Precision lung cancer screening from CT scans using a VGG16-based convolutional neural network.Front Oncol. 2024 Aug 19;14:1424546. doi: 10.3389/fonc.2024.1424546. eCollection 2024. Front Oncol. 2024. PMID: 39228981 Free PMC article.
-
Deciphering NF-kappaB pathways in smoking-related lung carcinogenesis.EXCLI J. 2024 Aug 19;23:991-1017. doi: 10.17179/excli2024-7475. eCollection 2024. EXCLI J. 2024. PMID: 39253534 Free PMC article. Review.
-
New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review.Front Oncol. 2023 Nov 29;13:1242392. doi: 10.3389/fonc.2023.1242392. eCollection 2023. Front Oncol. 2023. PMID: 38094613 Free PMC article. Review.
-
Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.Biofactors. 2025 Jan-Feb;51(1):e2129. doi: 10.1002/biof.2129. Epub 2024 Oct 16. Biofactors. 2025. PMID: 39415336 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical