![](https://dblp.dagstuhl.de/img/logo.ua.320x120.png)
![](https://dblp.dagstuhl.de/img/dropdown.dark.16x16.png)
![](https://dblp.dagstuhl.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.dagstuhl.de/img/search.dark.16x16.png)
![search dblp](https://dblp.dagstuhl.de/img/search.dark.16x16.png)
default search action
"Model-based and Unsupervised Machine-learning Approaches for the ..."
Marion Taconné et al. (2022)
- Marion Taconné, Virginie Le Rolle, Alban Gallard, Kimi P. Owashi, Adrien Al Wazzan, Elena Galli, Jens-Uwe Voigt, Jürgen Duchenne, Otto Smiseth, Erwan Donal, Alfredo I. Hernández:
Model-based and Unsupervised Machine-learning Approaches for the Characterization of Responder Profiles for Cardiac Resynchronization Therapy. CinC 2022: 1-4
![](https://dblp.dagstuhl.de/img/cog.dark.24x24.png)
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.