Deep learning for scene understanding in mitochondrial dysregulation and blood cancer diagnosis
Experimental results demonstrate significant improvements in classification performance, with our approach outperforming conventional machine learning and rule-based diagnostic systems. By leveraging deep learning for enhanced scene understanding, this work contributes to a more precise and scalable framework for the early detection and management of blood cancers.
Authors
- Zihan Liu (ORCID: https://orcid.org/0000-0001-6224-3823)
- Jianming Chang (ORCID: https://orcid.org/0000-0002-0052-6198)
- Feng Zhu (ORCID: https://orcid.org/0000-0001-6030-9251)
- Lulu Wang (ORCID: https://orcid.org/0000-0002-8575-4172)
- Yuanyuan Qin (ORCID: https://orcid.org/0000-0002-8168-3573)
Institutions
- Nanjing University of Chinese Medicine (CN)
- Pingdingshan University (CN)
- Southeast University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-13
- DOI
- https://doi.org/10.3389/fonc.2025.1609851
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00