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Plos One|September 19, 2022
A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classificationRaffaella Massafra, Maria Colomba Comes, Samantha Bove, et al.
BMC Health Services Research|May 23, 2023
Assessing the cost-effectiveness of waiting list reduction strategies for a breast radiology department: a real-life case studyAnnarita Fanizzi, Elisabetta Graps, Domenica Antonia Bavaro, et al.
Journal of Personalized Medicine|June 24, 2022
Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant ChemotherapyRaffaella Massafra, Maria Colomba Comes, Samantha Bove, et al.
Scientific Reports|June 20, 2024
Explainable prediction model for the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma using CNN on CT imagesAnnarita Fanizzi, Maria Colomba Comes, Samantha Bove, et al.
Cancers|May 14, 2022
An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort StudyRaffaella Massafra, Samantha Bove, Daniele La Forgia, et al.
Frontiers in Oncology|April 30, 2025
Validation of machine learning-based models to predict and explain the risk of ovarian cancer: a multicentric study on BRCA-mutated patients undergoing risk-reducing salpingo-oophorectomyVera Loizzi, Maria Colomba Comes, Francesca Arezzo, et al.
Scientific Reports|May 13, 2022
A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patientsSamantha Bove, Maria Colomba Comes, Vito Lorusso, et al.
Journal of Translational Medicine|September 12, 2024
An artificial intelligence-based model exploiting H&E images to predict recurrence in negative sentinel lymph-node melanoma patientsMaria Colomba Comes, Livia Fucci, Sabino Strippoli, et al.
Frontiers in Medicine|October 10, 2022
Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancerAnnarita Fanizzi, Giovanni Scognamillo, Alessandra Nestola, et al.
Frontiers in Medicine|December 9, 2022
Corrigendum: Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancerAnnarita Fanizzi, Giovanni Scognamillo, Alessandra Nestola, et al.
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