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Peer-reviewedCC BY 4.0Frontiers in Oncology

Editorial: AI-powered insights: predicting treatment response and prognosis in breast cancer

  • Tamer Ahmed Farrag1
  • Ashraf Elbatanony2
  • Mona Zaky3
  • Khaled Abdelwahab4
  • Yazan Masannat5
  • Mohamed Shehata6
  • Mostafa A. Elhosseini7,8
8 affiliations
  1. 1Department of Electrical Engineering, College of Engineering, Taif University
  2. 2Department of Cariology, Faculty of Medicine, Al Azhar University
  3. 3Diagnostic Radiology Department, Faculty of Medicine, Mansoura University
  4. 4Surgical Oncology Department, Mansoura Oncology Center, Mansoura University
  5. 5Bloomfield Hospital, Mid and South Essex NHS Foundation Trust
  6. 6Computer Science Major, James C. Bowling School of Business, Midway University
  7. 7Computers and Control Systems Engineering Department, Mansoura University, Faculty of Engineering
  8. 8Department of Information Systems, College of Computer Science and Engineering, Taibah University
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Cite

BibTeXRIS
BibTeX
@article{farrag2026editorial,
  title = {{Editorial: AI-powered insights: predicting treatment response and prognosis in breast cancer}},
  author = {Tamer Ahmed Farrag and Ashraf Elbatanony and Mona Zaky and Khaled Abdelwahab and Yazan Masannat and Mohamed Shehata and Mostafa A. Elhosseini},
  journal = {Frontiers in Oncology},
  year = {2026},
  month = oct,
  doi = {10.3389/fonc.2026.1996821},
  url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.1996821/full},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Editorial: AI-powered insights: predicting treatment response and prognosis in breast cancer
AU  - Tamer Ahmed Farrag
AU  - Ashraf Elbatanony
AU  - Mona Zaky
AU  - Khaled Abdelwahab
AU  - Yazan Masannat
AU  - Mohamed Shehata
AU  - Mostafa A. Elhosseini
PY  - 2026
DA  - 2026/10/29
JO  - Frontiers in Oncology
DO  - 10.3389/fonc.2026.1996821
UR  - https://www.frontiersin.org/articles/10.3389/fonc.2026.1996821/full
SN  - 2234-943X
ER  -