Advanced hybrid deep learning model for enhanced evaluation of osteosarcoma histopathology images
Using the Cancer Imaging Archive (TCIA) dataset, the model achieved an accuracy of 99.08%, precision of 99.10%, recall of 99.28%, and an F1-score of 99.23%. This is the first successful four-class classification using this dataset, setting a new benchmark in OS research and offering promising potential for future diagnostic advancements.
Authors
- Gernot Kronreif (ORCID: https://orcid.org/0000-0003-2675-2190)
- Sepideh Hatamikia
- Arezoo Borji (ORCID: https://orcid.org/0000-0003-1288-0976)
- Bernhard Angermayr
Institutions
- Danube Private University (AT)
- Universität für Weiterbildung Krems (AT)
- University of Applied Sciences St Pölten (AT)
- Austrian Center for Medical Innovation and Technology (AT)
- Universitätsklinikum St. Pölten (AT)
- Medical University of Vienna (AT)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-04-16
- DOI
- https://doi.org/10.3389/fmed.2025.1555907
- Citations
- 13
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 32.25
Funders
- Austrian Center for Medical Innovation and Technology