MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells.

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Bibliographic Details
Title: MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells.
Authors: Hinz S; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Grøndal SM; Department of Biomedicine & Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway., Miyano M; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Lopez JC; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Cotner KL; UC Berkeley-UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, CA, USA., Thomsen T; UC Berkeley-UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, CA, USA., Chen C; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., Hester EJ; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., Yee LD; Department of Surgery, City of Hope Comprehensive Cancer Center, Duarte, CA, USA., Seewaldt VE; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Lorens JB; Department of Biomedicine & Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway., Sohn LL; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., LaBarge MA; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA.; Center for Cancer and Aging Research, City of Hope, Duarte, CA, USA.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2025 Aug 12. Date of Electronic Publication: 2025 Aug 12.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.1101/2025.08.08.668946