"Prostate cancer therapy personalization via multi-modal deep learning on ..."

Andre Esteva et al. (2022)

> Home

Details and statistics

DOI: 10.1038/S41746-022-00613-W

access: open

type: Journal Article

metadata version: 2024-11-27

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/npjdm/EstevaFWHSDCSMS22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/npjdm/EstevaFWHSDCSMS22
Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad:
Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. npj Digit. Medicine 5 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.