Machine learning based anoikis signature predicts personalized treatment strategy of breast cancer
These findings highlight the critical role of anoikis in breast cancer prognosis and underscore AIDAS's potential to guide individualized treatment strategies. By integrating machine learning with biological insights, AIDAS offers a promising approach for advancing personalized oncology. Its detailed understanding of the anoikis landscape paves the way for the development of targeted therapies, promising significant improvements in patient outcomes.
Authors
- Runhong Mu (ORCID: https://orcid.org/0000-0003-3069-3381)
- Jiaying Xing
- Wenchuang Yang
- Tao Wang (ORCID: https://orcid.org/0000-0001-7087-4596)
- Xiao Guo
- Xinlin Shi (ORCID: https://orcid.org/0000-0003-4058-8067)
- Yuyan Cao (ORCID: https://orcid.org/0000-0003-3872-7523)
Institutions
- Beihua University (CN)
- Guizhou Provincial People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-11-22
- DOI
- https://doi.org/10.3389/fimmu.2024.1491508
- Citations
- 3
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.70