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Masahiro Yanagawa

Showing results (1-10 of 143) with videos related to

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Radiology|May 24, 2022
Artificial Intelligence Improves Radiologist Performance for Predicting Malignancy at Chest CTMasahiro Yanagawa
Radiology|July 5, 2022
Visualization of the Associations between the CT Features Extracted from a Deep Learning Survival Prediction Model and Histopathologic Risk FactorsMasahiro Yanagawa
Thoracic Surgery Clinics|November 13, 2010
Prediction of thymoma histology and stage by radiographic criteriaMasahiro Yanagawa, Noriyuki Tomiyama
Radiology|September 17, 2024
Transforming Lung Cancer Screening with AI: Comprehensive Evaluation and Personalized Medicine ProspectsMasahiro Yanagawa, Akinori Hata
Radiology|September 26, 2023
Clinical Performance of Current-Generation AI Tools for Chest RadiographsMasahiro Yanagawa, Noriyuki Tomiyama
Radiology. Artificial Intelligence|January 2, 2024
Seeing Is Not Always Believing: Discrepancies in Saliency MapsMasahiro Yanagawa, Junya Sato
Radiology. Artificial Intelligence|May 7, 2025
Better Data and Smarter AI: Automated Quality Control for Chest RadiographsMasahiro Yanagawa, Junya Sato
Radiology|August 5, 2020
CT Diagnosis of Lung Adenocarcinoma: Radiologic-Pathologic Correlation and Growth RateKeiko Kuriyama, Masahiro Yanagawa
AJR. American Journal of Roentgenology|April 10, 2024
The Global Reading Room: Purchasing a Radiology Artificial Intelligence SystemMerel Huisman, Felipe C Kitamura, John Mongan, et al.
Medical Physics|May 17, 2015
Erratum: "Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT" [Med. Phys. 42, 2054 (10pp.) (2015)]Adrien Depeursinge, Masahiro Yanagawa, Ann N Leung, et al.
Pageof 15

Showing results (1-10 of 143) with videos related to

Sort By:
Pageof 15
Radiology|May 24, 2022
Artificial Intelligence Improves Radiologist Performance for Predicting Malignancy at Chest CTMasahiro Yanagawa
Radiology|July 5, 2022
Visualization of the Associations between the CT Features Extracted from a Deep Learning Survival Prediction Model and Histopathologic Risk FactorsMasahiro Yanagawa
Thoracic Surgery Clinics|November 13, 2010
Prediction of thymoma histology and stage by radiographic criteriaMasahiro Yanagawa, Noriyuki Tomiyama
Radiology|September 17, 2024
Transforming Lung Cancer Screening with AI: Comprehensive Evaluation and Personalized Medicine ProspectsMasahiro Yanagawa, Akinori Hata
Radiology|September 26, 2023
Clinical Performance of Current-Generation AI Tools for Chest RadiographsMasahiro Yanagawa, Noriyuki Tomiyama
Radiology. Artificial Intelligence|January 2, 2024
Seeing Is Not Always Believing: Discrepancies in Saliency MapsMasahiro Yanagawa, Junya Sato
Radiology. Artificial Intelligence|May 7, 2025
Better Data and Smarter AI: Automated Quality Control for Chest RadiographsMasahiro Yanagawa, Junya Sato
Radiology|August 5, 2020
CT Diagnosis of Lung Adenocarcinoma: Radiologic-Pathologic Correlation and Growth RateKeiko Kuriyama, Masahiro Yanagawa
AJR. American Journal of Roentgenology|April 10, 2024
The Global Reading Room: Purchasing a Radiology Artificial Intelligence SystemMerel Huisman, Felipe C Kitamura, John Mongan, et al.
Medical Physics|May 17, 2015
Erratum: "Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT" [Med. Phys. 42, 2054 (10pp.) (2015)]Adrien Depeursinge, Masahiro Yanagawa, Ann N Leung, et al.
Pageof 15