default author photo

Jun Matsubayashi

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

1

DOWNLOADS

59

TOTAL CITATIONS

0

Scholarly Papers (1)

Actions:
Email selected abstracts
1.

Prognostic Impact of Artificial Intelligence-Based Volumetric Quantification of the Solid Part of the Tumor in Clinical Stage I Adenocarcinoma

Number of pages: 27 Posted: 02 May 2022
Yohei Kawaguchi, Yoshihisa Shimada, Kotaro Murakami, Tomokazu Omori, Yujin Kudo, Yojiro Makino, Sachio Maehara, Masaru Hagiwara, Masatoshi Kakihana, Takafumi Yamada, Jun Matsubayashi, Tatsuo Ohira and Norihiko Ikeda
University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, University of Tokyo - Department of Surgery, Tokyo Medical University - Department of General Thoracic Surgery, affiliation not provided to SSRN, affiliation not provided to SSRN, Tokyo Medical University and Tokyo Medical University
Downloads 59 (970,490)

Abstract:

Loading...

Artificial intelligence, three-dimensional convolutional network, part-solid nodule, adenocarcinoma, three-dimensional volumetric analysis.