Radiologists Versus AI-Based Software: Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma From CT Under Various Image Display Conditions
Radiologists' CT measurements were significant predictors of LNM and prognosis, but variability existed among radiologists and display conditions. AI-based software can provide accurate and reproducible indicators for predicting LNM and prognosis.
Authors
- Shoji Kido (ORCID: https://orcid.org/0000-0001-5293-4110)
- Yukinori Sakao (ORCID: https://orcid.org/0000-0002-6826-2280)
- Daiki Nishigaki (ORCID: https://orcid.org/0000-0002-7006-3408)
- Noriyuki Tomiyama (ORCID: https://orcid.org/0000-0001-9918-7327)
- Junya Sato (ORCID: https://orcid.org/0000-0002-1206-2036)
- Yasushi Yatabe (ORCID: https://orcid.org/0000-0003-1788-559X)
- Yasushi Shintani (ORCID: https://orcid.org/0000-0002-2540-5288)
- Akinori Hata (ORCID: https://orcid.org/0000-0003-1149-7094)
- Masahiro Yanagawa (ORCID: https://orcid.org/0000-0002-0911-6769)
- Noriaki Sakakura (ORCID: https://orcid.org/0000-0002-9598-9629)
Institutions
- Osaka City University (JP)
- Aichi Cancer Center (JP)
- National Cancer Center Hospital East (JP)
- Tokyo National Hospital (JP)
- Teikyo University (JP)
- The University of Osaka (JP)
Publication Details
- Journal
- Clinical Lung Cancer
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1016/j.cllc.2024.10.015
- Citations
- 2
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.84
Funders
- Japan Science and Technology Agency