"Discovering Key Topics From Short, Real-World Medical Inquiries via ..."

Angelo Ziletti et al. (2021)

> Home

Details and statistics

DOI: 10.3389/FCOMP.2021.672867

access: open

type: Journal Article

metadata version: 2021-10-25

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/fcomp/ZilettiBTWLKSVR21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/fcomp/ZilettiBTWLKSVR21
Angelo Ziletti, Christoph Berns, Oliver Treichel, Thomas Weber, Jennifer Liang, Stephanie Kammerath, Marion Schwaerzler, Jagatheswari Virayah, David Ruau, Xin Ma, Andreas Mattern:
Discovering Key Topics From Short, Real-World Medical Inquiries via Natural Language Processing. Frontiers Comput. Sci. 3: 672867 (2021)

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.