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For: Rozen R, Weihs D. Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay. Ann Biomed Eng 2021;49:1774-83. [PMID: 33483841 DOI: 10.1007/s10439-020-02720-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 12/30/2020] [Indexed: 12/13/2022]
Number Cited by Other Article(s)
1
Tulchinsky M, Weihs D. Mechanobiological cell adaptations to changing microenvironments determine cancer invasiveness: Experimentally validated finite element modeling. J Biomed Mater Res A 2023;111:1951-1959. [PMID: 37606496 DOI: 10.1002/jbm.a.37597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/30/2023] [Accepted: 08/11/2023] [Indexed: 08/23/2023]
2
Modeling force application configurations and morphologies required for cancer cell invasion. Biomech Model Mechanobiol 2021;20:1187-1194. [PMID: 33683515 DOI: 10.1007/s10237-021-01441-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/17/2021] [Indexed: 10/24/2022]
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