Loading clinical trials...
Loading clinical trials...
Browse 4,817 clinical trials for breast cancer. Find studies that match your criteria and connect with research centers.
Find trials near:
Showing 581-600 of 4,817 trials
NCT07344597
To compare the efficacy and safety of two hypofractionated adjuvant radiotherapy regimens 34 Gy in 10 fractions versus 40.05 Gy in 15 fractions in patients with breast cancer treated at the South Egypt Cancer Institute.
NCT07341542
A prospective clinical study investigating the use of the Histolog Scanner for intraoperative assessment of surgical margins in patients undergoing breast-conserving surgery for histologically confirmed breast cancer. The Histolog Scanner operates on the principle of confocal microscopy and enables non-destructive evaluation of specimen margins. The specimen will subsequently be sent for standard histopathological assessment; therefore, the use of this method does not pose any risk to the patient, as the diagnostic and therapeutic pathway for breast cancer will not be altered.
NCT07298252
This study evaluates the diagnostic performance of Carebot AI MMG, an artificial intelligence (AI)-enabled medical device for evaluating mammograms. The software analyzes standard full-field digital mammography (FFDM) images and classifies each examination as having no suspicious finding ("Low Risk"), a probably benign mass ("Medium Risk"), or a suspicious malignant mass ("High Risk"). The study is retrospective and observational. It uses anonymized mammography examinations from four screening centers, without any additional imaging or contact with patients. Three experienced breast radiologists independently read the same set of cases, and their assessments are used as the human benchmark. A histopathology-based reference standard, supplemented by radiologist consensus and follow-up information for negative cases, is used to determine whether cancer is present. The main goal is to compare the AI system with human radiologists in terms of sensitivity and specificity for detecting breast cancer, and to assess whether the AI can achieve non-inferior performance at two predefined operating points: one favoring higher sensitivity and negative predictive value (rule-out) and one favoring higher specificity and positive predictive value (rule-in).