A convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models
This approach can enhance personalized cancer treatment by providing non-invasive, reliable predictions of therapeutic outcomes.
Authors
- Chrysovalantis Voutouri (ORCID: https://orcid.org/0000-0003-3172-9489)
- Giorgos Papanastasiou (ORCID: https://orcid.org/0000-0002-1939-296X)
- Triantafyllos Stylianopoulos (ORCID: https://orcid.org/0000-0002-3093-1696)
- Demetris Englezos
- Iosif Strouthos (ORCID: https://orcid.org/0000-0001-6229-5471)
- Constantinos Zamboglou (ORCID: https://orcid.org/0000-0002-7849-7550)
Institutions
- University of Essex (GB)
- University of Freiburg (DE)
- German Cancer Research Center (DE)
- European University Cyprus (CY)
- University Medical Center Freiburg (DE)
- University of Cyprus (CY)
- Athena Research and Innovation Center In Information Communication & Knowledge Technologies (GR)
- Deutsches Konsortium für Translationale Krebsforschung (DE)
Publication Details
- Journal
- Communications Medicine
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1038/s43856-024-00634-4
- Citations
- 10
- Primary Topic
- Ultrasound Imaging and Elastography
- Type
- article
- Field-Weighted Citation Impact
- 4.04
Funders
- European Commission