Use of Deep Learning Networks and Statistical Modeling to Predict Changes in Mechanical Parameters of Contaminated Bone Cements.

Machrowska, Anna; Szabelski, Jakub; Karpinski, Robert; Krakowski, Przemyslaw; Jonak, Józef; Jonak, Kamil

Machrowska, Anna; Szabelski, Jakub; Karpinski, Robert; Krakowski, Przemyslaw; Jonak, Józef; Jonak, Kamil.

Afiliação

Machrowska A; Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland.
Szabelski J; Section of Biomedical Engineering, Department of Computerization and Production Robotization, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland.
Karpinski R; Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland.
Krakowski P; Chair and Department of Traumatology and Emergency Medicine, Medical University of Lublin, Staszica 11, 20-081 Lublin, Poland.
Jonak J; Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland.
Jonak K; Department of Clinical Neuropsychiatry, Medical University of Lublin, 20-439 Lublin, Poland.

Materials (Basel) ; 13(23)2020 Nov 28.

Article em En | MEDLINE | ID: mdl-33260793

Palavras-chave

bone cement; deep learning networks (DLN); prediction, mechanical parameters, compressive strength; statistical modeling

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Polônia País de publicação: Suíça

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