Artificial Intelligence, Radiomics, and Deep Learning in Neuro-Oncology

Radiomics and Deep Learning

Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching, or even exceeding, the human level on an increasing number of complex tasks. Impressive examples of this development can be found in domains such as image classification, sentiment analysis, speech understanding or strategic game playing. However, because of ...

Deep Reinforcement Learning as Foundation for Artificial General Intelligence

Deep machine learning and reinforcement learning are two complementing fields within the study of intelligent systems. When combined, it is argued that they offer a promising path for achieving artificial general intelligence (AGI). This chapter outlines the concepts facilitating such merger of technologies and motivates a framework for building scalable intelligent machines. The prospect of ut...

An Artificial Intelligence Based Neuro-Fuzzy System with Emotional Intelligence

In a very real sense we have two minds, one that thinks (rational mind) and one that feels (emotional mind). These two fundamentally different ways of knowing interact to construct our mental life. This results in two different kinds of intelligence i.e, rational and emotional. Intellect cannot work at its best without emotional intelligence. If our aim in AI is to build systems that behave lik...

Biological Learning and Artificial Intelligence

It was once taken for granted that learning in animals and man could be explained with a simple set of general learning rules, but over the last hundred years, a substantial amount of evidence has been accumulated that points in a quite different direction. In animal learning theory, the laws of learning are no longer considered general. Instead, it has been necessary to explain behaviour in te...