A Machine Learning Model Based on MRI Radiomics to Predict Response to Chemoradiation Among Patients with Rectal Cancer
These results highlight the potential of radiomics and machine learning in predicting treatment response and support the integration of advanced imaging and computational methods for personalized rectal cancer management.
Authors
- Christian Salvatore (ORCID: https://orcid.org/0000-0001-9312-4675)
- Carlo D’Alessandro
- Salvatore Pucciarelli (ORCID: https://orcid.org/0000-0001-5289-9925)
- Emilio Quaia (ORCID: https://orcid.org/0000-0003-2020-9365)
- Isabella Castiglioni (ORCID: https://orcid.org/0000-0001-7191-5417)
- Filippo Crimì (ORCID: https://orcid.org/0000-0001-6822-1430)
- Francesco Celotto (ORCID: https://orcid.org/0000-0002-1881-0605)
- Gaya Spolverato (ORCID: https://orcid.org/0000-0002-7275-2573)
- Chiara Zanon (ORCID: https://orcid.org/0000-0002-7917-5027)
- Matteo Interlenghi (ORCID: https://orcid.org/0000-0002-3066-4276)
Institutions
- University of Padua (IT)
- Istituto Universitario di Studi Superiori di Pavia (IT)
- University of Milano-Bicocca (IT)
Publication Details
- Journal
- Life
- Published
- 2024-11-22
- DOI
- https://doi.org/10.3390/life14121530
- Citations
- 4
- Primary Topic
- Colorectal Cancer Surgical Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.13