Publications by authors named "I Allajbeu"
Aims: To establish the safety and feasibility of delivering neoadjuvant radiotherapy and endocrine therapy for oestrogen receptor-positive breast cancers with palpable size 20mm or greater, for which radiotherapy might facilitate more conservative surgery.
Materials And Methods: A single-arm feasibility study was conducted. Patients received whole breast radiotherapy with or without radiotherapy to nodal areas.
Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. Purpose To evaluate AI localizations of interval cancers (ICs) on screening mammograms by IC category and histopathologic characteristics. Materials and Methods A screening mammography data set (median patient age, 57 years [IQR, 52-64 years]) that had been assessed by two human readers from January 2011 to December 2018 was retrospectively analyzed using a commercial AI system.
View Article and Find Full Text PDFArticle Synopsis
- The study aimed to evaluate the effectiveness of a deep learning model for automatically segmenting pelvic/ovarian and omental lesions in high-grade serous ovarian cancer on CT scans.
- Using 451 CT scans for training, evaluation, and testing, the model was compared against existing methods and trainee radiologist segmentations.
- Results indicated that the deep learning model significantly outperformed the standard method for pelvic/ovarian lesions and performed comparably to a trainee radiologist, suggesting that automated segmentation is a viable tool in clinical settings.
Background: Pathological response to neoadjuvant treatment for patients with high-grade serous ovarian carcinoma (HGSOC) is assessed using the chemotherapy response score (CRS) for omental tumor deposits. The main limitation of CRS is that it requires surgical sampling after initial neoadjuvant chemotherapy (NACT) treatment. Earlier and non-invasive response predictors could improve patient stratification.
View Article and Find Full Text PDF