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Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future
Michaela Cellina1, Maurizio Cè2, Giovanni Irmici2
1Radiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Milano, Piazza Principessa Clotilde 3, 20121 Milan, Italy.
Diagnostics (Basel, Switzerland)
|November 11, 2022
Summary
Artificial intelligence (AI) in lung cancer imaging aids early detection and personalized treatment. AI tools analyze imaging data for nodule detection, risk assessment, and predicting patient outcomes and treatment response.
Area of Science:
- Oncology
- Radiology
- Artificial Intelligence
Background:
- Lung cancer presents significant morbidity and mortality.
- Medical imaging is crucial throughout lung cancer management.
- Artificial intelligence (AI) is emerging as a transformative tool in oncology.
Purpose of the Study:
- To review AI-based imaging tools for lung cancer.
- To highlight AI's role in early detection and treatment planning.
- To provide a foundation for clinical AI applications in lung cancer.
Main Methods:
- Review of current AI applications in lung cancer imaging.
- Analysis of AI for automated lesion detection and characterization.
- Evaluation of AI for segmentation, outcome prediction, and treatment response assessment.
Main Results:
- AI significantly enhances early lung nodule detection in screening programs.
- AI models integrate imaging with clinical data for improved risk prediction.
- AI shows promise in predicting patient outcomes and treatment efficacy.
Conclusions:
- AI-powered imaging tools are revolutionizing lung cancer management.
- AI facilitates personalized screening and treatment strategies.
- AI integration offers a robust foundation for clinical radiologists and clinicians.
