Machine learning-based approach for automated classification of cell and extracellular matrix using nanomechanical properties.

"data availability data will be made available on request. acknowledgment graphical abstract was created with biorender com . appendix a supplementary data to this article can be found online at https://doi"

"Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper."

"Funding This work is supported partly by 10.13039/100000002National Institutes of Health grants CA78383, CA150190, and NS129671-01, 10.13039/100000050NHLBI (#HL140411) and 10.13039/100006827Florida Department of Health (Cancer Research Chair Fund, Florida #3J) and 10.13039/100006827Florida Department of Health Grant #20K02 to DM and 10.13039/100000871Mayo Clinic Pancreatic Cancer SPORE Career Enhancement Award, Eagles fifth District Cancer Telethon−Cancer Research Fund and Jay and Deanie Stein Career Development Award for Cancer Research at 10.13039/100000871Mayo Clinic Jacksonville, 2019 Benefactor Funded Champions for Hope Pancreatic Cancer to SB."