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Automatic inference model construction for computer-aided diagnosis of lung nodule: Explanation adequacy, inference accuracy, and experts' knowledge.
Kawagishi M, Kubo T, Sakamoto R, Yakami M, Fujimoto K, Aoyama G, Emoto Y, Sekiguchi H, Sakai K, Iizuka Y, Nishio M, Yamamoto H, Togashi K. Kawagishi M, et al. Among authors: yakami m. PLoS One. 2018 Nov 16;13(11):e0207661. doi: 10.1371/journal.pone.0207661. eCollection 2018. PLoS One. 2018. PMID: 30444907 Free PMC article.
Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning.
Nishio M, Sugiyama O, Yakami M, Ueno S, Kubo T, Kuroda T, Togashi K. Nishio M, et al. Among authors: yakami m. PLoS One. 2018 Jul 27;13(7):e0200721. doi: 10.1371/journal.pone.0200721. eCollection 2018. PLoS One. 2018. PMID: 30052644 Free PMC article.
A study of computer-aided diagnosis for pulmonary nodule: comparison between classification accuracies using calculated image features and imaging findings annotated by radiologists.
Kawagishi M, Chen B, Furukawa D, Sekiguchi H, Sakai K, Kubo T, Yakami M, Fujimoto K, Sakamoto R, Emoto Y, Aoyama G, Iizuka Y, Nakagomi K, Yamamoto H, Togashi K. Kawagishi M, et al. Among authors: yakami m. Int J Comput Assist Radiol Surg. 2017 May;12(5):767-776. doi: 10.1007/s11548-017-1554-0. Epub 2017 Mar 11. Int J Comput Assist Radiol Surg. 2017. PMID: 28285338
30 results