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Applying patient characteristics, stent-graft selection, and pre-operative computed tomographic angiography data to a machine learning algorithm: Is endoleak prediction possible?

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Title: Applying patient characteristics, stent-graft selection, and pre-operative computed tomographic angiography data to a machine learning algorithm: Is endoleak prediction possible?
Authors: Masuda T; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan. Electronic address: takanorimasuda@yahoo.co.jp., Baba Y; Department of Diagnostic Radiology, Saitama Medical University International Medical Center, 1397-1, Yamane, Hidaka-City, Saitama-Pref 350-1298, Japan., Nakaura T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto 860-8556, Japan., Funama Y; Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Kumamoto, 1-1-1 Honjo, Kumamoto 860-8556, Japan., Sato T; Department of Diagnostic Radiology, Tsuchiya General Hospital, Nakajima-cho 3-30, Naka-ku, Hiroshima 730-8655, Japan., Masuda S; Department of Radiological Technology, Kawamura Clinic, Otemachi, Naka-ku, Hiroshima 730-0051, Japan., Gotanda R; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Arao K; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Imaizumi H; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Arao S; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Ono A; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Hiratsuka J; Department of Radiological Technology, Faculty of Health Science and Technology, Kawasaki University of Medical Welfare, 288, Matsushima, Kurashiki, Okayama, 701-0193, Japan., Awai K; Department of Diagnostic Radiology, Graduate School of Biomedical Sciences, Hiroshima University, Kasumi 1-2-3 Minami-ku, Hiroshima 734-8551, Japan.
Source: Radiography (London, England : 1995) [Radiography (Lond)] 2022 Nov; Vol. 28 (4), pp. 906-911. Date of Electronic Publication: 2022 Jul 01.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier B.V Country of Publication: Netherlands NLM ID: 9604102 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-2831 (Electronic) Linking ISSN: 10788174 NLM ISO Abbreviation: Radiography (Lond) Subsets: MEDLINE
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