Title |
An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis / Christoph Römmele, Robert Mendel, Caroline Barrett, Hans Kiesl, David Rauber, Tobias Rückert, Lisa Kraus, Jakob Heinkele, Christine Dhillon, Bianca Grosser, Friederike Prinz, Julia Wanzl, Carola Fleischmann, Sandra Nagl, Elisabeth Schnoy, Jakob Schlottmann, Evan S. Dellon, Helmut Messmann, Christoph Palm, Alanna Ebigbo |
|---|---|
Involved |
Christoph Römmele (Verfasser)
Robert Mendel (Verfasser) Caroline Barrett (Verfasser) Hans Kiesl (Verfasser)
David Rauber (Verfasser)
Tobias Rückert (Verfasser) Lisa Kraus (Verfasser) Jakob Heinkele (Verfasser) Christine Dhillon (Verfasser) Bianca Grosser (Verfasser) Friederike Prinz (Verfasser) Julia Wanzl (Verfasser) Carola Fleischmann (Verfasser) Sandra Nagl (Verfasser) Elisabeth Schnoy (Verfasser) Jakob Schlottmann (Verfasser) Evan S. Dellon (Verfasser) Helmut Messmann (Verfasser) Christoph Palm (Verfasser) Alanna Ebigbo (Verfasser) |
Published |
Regensburg: Ostbayerische Technische Hochschule Regensburg |
Extent |
Online-Ressource |
Language |
|
Country |
|
Topic |
|
Subject |
Artificial Intelligence |
DDC notation |
|
Persistent identifier |
|
Further information |
In: Scientific Reports, 12, 10 S. |
Record ID |
1263104177 |
Please note
The beta version does not yet contain all functions and information of the DNB portal catalogue. If you are missing information or want to order a medium, please visit the page in the DNB portal catalogue via the following link: