Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer
Incorporating clinical and imaging features along with dose descriptors are beneficial for predicting cardiotoxicity after radiotherapy.
Authors
- Meysam Tavakoli (ORCID: https://orcid.org/0000-0002-7475-2139)
- Benyamin Khajetash (ORCID: https://orcid.org/0000-0002-3604-2451)
- Ghasem Hajianfar (ORCID: https://orcid.org/0000-0001-5359-2407)
- Azin Alizadehasl (ORCID: https://orcid.org/0000-0002-8550-1378)
- Parisa Seilani
- Ahmad Bitarafan‐Rajabi (ORCID: https://orcid.org/0000-0002-1596-6292)
- Amin Talebi
Institutions
- Emory University (US)
- Iran University of Medical Sciences (IR)
- Piedmont Cancer Institute (US)
- University Hospital of Geneva (CH)
- Shaheed Rajaei Cardiovascular Medical and Research Center (IR)
Publication Details
- Journal
- Journal of Applied Clinical Medical Physics
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1002/acm2.14614
- Citations
- 17
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 6.87