… In oncology research, deep learning has demonstrated initial success in cell … cell carcinoma
(SCC), the most common type of oral cancer, deep learning has been used to categorize cell …

… The purpose of the study was to provide a comprehensive review of recent machine learning
(ML) and deep learning (DL) applications in urological practice. Numerous studies have …

… evaluates a deep learning architecture for automated basal cell carcinoma cancer detection
… representation learning and deep learning [10] and yields a deep learning architecture that …

… In this study, we demonstrate how deep learning framework can be used for an automatic
classification of Renal Cell Carcinoma (RCC) subtypes, and for identification of features that …

… We aimed to develop a rapid, non-invasive, cost-effective, and easy-to-use deep learning
approach for identifying oral cavity squamous cell carcinoma (OCSCC) patients using …

… We are currently in the process of developing the deep learning system based on NBI images
to establish a more subjective method that combines the current white-light algorithm with …

… review of deep learning in RCC applications. This review aims to show that deep learning
… to meet us for the mutual benefit of renal cell carcinoma patients. Medical imaging plays an …

… and validate deep-learning-based models for grading clear cell renal cell carcinoma (ccRCC) …
Here, we demonstrated a deep learning(DL) framework initialized by a self-supervised pre-…

… a high-performing deep learning model. Early work on deep learning for medical imaging
mainly … In this study, the deep learning model used a training dataset collected in 2017, and …

… In this study, we developed and evaluated a deep learning–based artificial intelligence
model to automatically detect BCC in reflectance confocal microscopy images. The proposed …