In addition, per study inclusion criteria, all participants had to have a prior mammogram to determine breast density but could not have had a prior breast MRI. Therefore, all of the DBT studies but none of the abbreviated breast MRI studies were interpreted with prior imaging for comparison—...
of synthetic image patches at a high resolution of 256 × 256 pixels. The resulting ciGAN model was then applied to GAN-based augmentation, which improved mammogram patch-based classification by 0.014 AUC over the baseline model and 0.009 AUC over traditional augmentation techniques66. This stu...
evaluation of explanations through auxiliary tasks required additional manual efforts to get the necessary ground truth annotations. Properties of the explanation itself were also quantified as their usefulness to identify risky and safe predictions at a voxel-level for the main task by thresholding on ...
In an example, the first AI-based system 120 may be configured to cross-correlate input sample and results of different medical diagnosis tests, such as X-rays, mammogram, genetic screening test, MRI, blood tests, etc., conducted from the plurality of different medical equipment 114. The ...
Transparency in Machine Learning (ML), often also referred to as interpretability or explainability, attempts to reveal the working mechanisms of complex models. From a human-centered design perspective, transparency is not a property of the ML model but
Therefore, an annual mammogram is necessary for women, especially after the age of 45 [4]. The number of new cases in Malaysia reported by the International Agency for Research on Cancer in 2020 [5] was 8418 per 100,000 individuals (32%). Breast cancer is the most common cancer among ...
The ETECADx has a capability to predict the breast lesions for a single mammogram in an average of 0.048 s. Such promising performance could be useful and helpful to assist the practical CAD framework applications providing a second supporting opinion of distinguishing various breast cancer ...