On deep learning for medical image analysis

Neural networks, a subclass of methods in the broader field of machine learning, are highly effective in enabling computer systems to analyze data, facilitating thework of clinicians. Neuralnetworks have beenusedsincethe1980s,withconvolutionalneuralnetworks(CNNs) applied to images beginning in the 1990s.1-3 Examples include identifying natural images of everyday life,4 classifying retinal pathology,5 selectingcellular elements on pathological slides,6 andcorrectly identifyingthe spatial orientation ofchest radiographs.7 Successful neural networks for such tasks are typically composed of multiple analysis layers; the term deep learning is also (synonymously) used to describe this class of neural networks.