Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …

Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Background An increasing volume of prostate biopsies and a worldwide shortage of
urological pathologists puts a strain on pathology departments. Additionally, the high intra …

For prostate cancer patients, the Gleason score is one of the most important prognostic
factors, potentially determining treatment independent of the stage. However, Gleason …

The Gleason grading system remains the most powerful prognostic predictor for patients
with prostate cancer since the 1960s. Its application requires highly-trained pathologists, is …

There has been an exponential growth in the application of AI in health and in pathology.
This is resulting in the innovation of deep learning technologies that are specifically aimed at …

Deep learning (DL) is a powerful methodology for the recognition and classification of tissue
structures in digital pathology. Its performance in prostate cancer pathology is still under …

Histopathological images contain morphological markers of disease progression that have
diagnostic and predictive values. In this study, we demonstrate how deep learning …

Abstract Background and Objective Prostate cancer is one of the most common diseases
affecting men worldwide. The Gleason scoring system is the primary diagnostic and …