Yeah, with the renaissance that image analysis is undergoing in the last few years with DNNs, to say anything is impossible is showing a lack of imagination.
anyways, that's not my point. i'm saying deep learning for image analysis has been a huge success, and people should explore ways to apply this success to medical imaging.
but just for your info, neural networks are slowly being generalized to a lot of other challenges. look around for topics on recurrent neural networks, memory networks, reinforcement learning, etc etc. i don't think we've fully finished exploring the many ways neural networks can help solve life's challenges just yet.
Go is a much harder problem in large part because it's really hard to accurately classify which board is better off.
Teaching Deep Convolutional Neural Networks to Play Go: "Our convolutional neural networks can consistently defeat the well known Go program GNU Go... It is also able to win some games against state of the art Go playing program Fuego while using a fraction of the play time." http://arxiv.org/abs/1412.3409