Pathology AI: Deep Learning vs Decision Trees - Flagship Biosciences

February 19, 2019 – Machine learning, which provides the ability to learn a task from data (without the need of being programmed explicitly), is a key component of any Pathology AI (Artificial Intelligence) system. There are many different approaches in machine learning, reaching from simple decision trees to complex deep learning, each with its advantages and disadvantages. Deep learning, which allows to learn highly complex visual features, has created a hype about Artificial Intelligence (AI) and Healthcare AI, as is was able to solve complex computer vision problems that we believed out-of-reach just a few years ago. As pathology is a visual task it is understandable that academia and "pure" technology companies are now working heavily on deep learning approaches for pathology.The key problem for any Pathology AI system are the variations between different patient types. In a disease state, no two patient samples look identical.