… of radiology and pathology, but … of deep learning, the most popular AI technology, on cancer
radiology. Next, we will introduce the new advance of AI tech applied in the cancer pathology…

… Then, we provide an overview of the primary datasets of histopathological diagnosis. We …
the main works surveyed and identifies challenges for future research. To make deep learning-…

… Our LSFM study therefore sets a … with deep learning computational methods for fast processing
of big data represents an ideal technology for absolute quantification of histopathological …

… to study neurodegeneration. The spatial and temporal features, when used to train convolutional
neural networks, … proteinopathies, such as Tau pathology in both ALS and Parkinson’s …

… method was used to construct and train a deep neural network model. … based on deep learning
technology developed in this study … ; Non-alcoholic fatty liver diagnosis; Digital pathology …

… cancer from routine histology images: a retrospective study[J]. … visual feature learning with
deep neural networks: A survey[J]… image computing, computational pathology, digital pathology…

… 计算流体力学(computational fluid dynamics, CFD) … convolutional neural network can calculate
the corresponding results within 10 milliseconds with a relatively high accuracy. This study …

… 而近些年,基于深度学习(Deep Learning, DL) 的 色彩迁移技术作为一种极具发展潜力的色彩迁移
技 术已经… Virtually colorizing deep neural network Virtually colorizing deep neural network …

… of histopathology WSIs is the gold standard for pathology … begun exploring the application
of deep learning in the field of … Result This study performs a comparison and ablation-related …

… 级 的卷积神经网络( convolutional neural network, CNN). 除玻… Aprognosticandpredic⁃ tive
computational pathology image … histopathological images using multiscale deep learning [J]. …