Artificial intelligence-based radiomics for the prediction of nodal metastasis in early-stage lung cancer.

Shimada, Yoshihisa; Kudo, Yujin; Maehara, Sachio; Fukuta, Kentaro; Masuno, Ryuhei; Park, Jinho; Ikeda, Norihiko

Shimada, Yoshihisa; Kudo, Yujin; Maehara, Sachio; Fukuta, Kentaro; Masuno, Ryuhei; Park, Jinho; Ikeda, Norihiko.

Affiliation

Shimada Y; Department of Thoracic Surgery, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-Ku, Tokyo, 160-0023, Japan. zenkyu@za3.so-net.ne.jp.
Kudo Y; Department of Thoracic Surgery, Tokyo Medical University, Tokyo, Japan.
Maehara S; Department of Thoracic Surgery, Tokyo Medical University, Tokyo, Japan.
Fukuta K; Department of Thoracic Surgery, Tokyo Medical University, Tokyo, Japan.
Masuno R; Department of Radiology, Tokyo Medical University, Tokyo, Japan.
Park J; Department of Radiology, Tokyo Medical University, Tokyo, Japan.
Ikeda N; Department of Thoracic Surgery, Tokyo Medical University, Tokyo, Japan.

Sci Rep ; 13(1): 1028, 2023 01 19.

Article de En | MEDLINE | ID: mdl-36658301

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Épithélioma in situ / Carcinome pulmonaire non à petites cellules / Tumeurs du poumon Type d'étude: Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: Sci Rep Année: 2023 Type de document: Article Pays d'affiliation: Japon Pays de publication: Royaume-Uni

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