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State-of-the-art artificial intelligence methods for pre-operative planning of cardiothoracic surgery and interventions: a narrative review

Mank, Quinten J., Thabit, Abdullah, Maat, Alexander P. W. M., Siregar, Sabrina, Mahtab, Edris A. F., van Walsum, Theo, Sadeghi, Amir H., Kluin, Jolanda·2025·Journal of Thoracic Disease
DOI 10.21037/jtd-24-1793PMC PMC12340272
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  • AI-powered imaging analysis and radiomics have improved detection and classification of pulmonary nodules, prediction of lymph node metastasis, and integration of molecular and radiomic features for non-invasive stratification.

    “AI-powered imaging analysis and radiomics have improved detection and classification of pulmonary nodules, prediction of lymph node metastasis, and integration of molecular and radiomic features for non-invasive stratification [4,5,6].”

    From Artificial Intelligence in Oncologic Thoracic Surgery: Clinical Decision Support and Emerging Applications (2026) · cites this paper as [4]

    The Introduction reports AI detection and classification of lung nodules, and Results > Lung, thoracic wall and mediastinal surgery reports CT-based classification of lung adenocarcinoma and improved diagnostic performance from combining conventional and radiomic features for mediastinal tumors (page numbers unavailable). Our copy does not report prediction of lymph node metastasis or integration of molecular and radiomic features for non-invasive stratification. (LLM, conf=0.87)

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Cited by

Sorted by citations

Authors
Mank, Q. J., Thabit, A., Maat, A. P. W. M., Siregar, S., Mahtab, E. A. F., van Walsum, T., Sadeghi, A. H., & Kluin, J.
Venue
Journal of Thoracic Disease
Publisher
AME Publishing Company
Published
2025-07
Volume
17
Issue
7
Pages
5282-5297
ISSN
  • 2072-1439
  • 2077-6624
DOI
10.21037/jtd-24-1793
PMC
PMC12340272
Cited by
13
References
0

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