The integration of convolutional neural networks into dermatology practices, especially those with fewer than 5 years of experience, may increase diagnostic accuracy of skin cancer, according to a ...

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural ...

Melanoma probability scores increased due to standard skin markings from surgical ink and were associated with a significant reduction in the specificity of a convolutional neural network trained ...

Researchers have shown for the first time that a form of artificial intelligence or machine learning known as a deep learning convolutional neural network (CNN) is better than experienced ...

Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network–Based Artificial Intelligence Tool The best performing model, a Bi-LSTM NER ...

Lung cancer is responsible for taking the lives of 1.6 million people per year. ... Through the use of convolutional neural networks accelerated by Nvidia Tesla GPU accelerators, ...

The innovative use of MAC-Net, a multiple instance convolutional neural network (MICNN) with modality-based attention (MA) and contextual MIL pooling layer (C-MPL), may overcome shortcomings of ...