Artificial Intelligence and Deep Learning in Pathology

<ol> <li>The evolution of machine learning: past, present, and future</li> <p>Stanley Cohen</p> <p> <li>The basics of machine learning: strategies and techniques</li> <p>Stanley Cohen</p> <p> <li>Overview of advanced neural network architectures</li> <p>Benjamin R. Mitchell</p> <p> <li>Complexity in the use of artificial intelligence in anatomic pathology</li> <p>Stanley Cohen</p> <p> <li>Dealing with data: strategies of preprocessing data</li> <p>Stanley Cohen</p> <p> <li>Digital pathology as a platform for primary diagnosis and augmentation via deep learning.</li> <p>Anil V. Parwani</p> <p> <li>Applications of artificial intelligence for image enhancement in pathology </li> <p>Tanishq Abraham, Austin Todd, Daniel A. Orringer and Richard Levenson</p> <p> <li>Precision medicine in digital pathology via image analysis and machine learning</li> <p>Peter D. Caie, Neofytos Dimitriou and Ognjen Arandjelovi'c</p> <p> <li>Artificial intelligence methods for predictive image-based grading of human cancers</li> <p>Gerardo Fernandez, Abishek Sainath Madduri, Bahram Marami, Marcel Prastawa, Richard Scott, Jack Zeineh and Michael Donovan</p> <p> <li>Artificial intelligence and the interplay between tumor and immunity</li> <p>Joel Haskin Saltz and Rajarsi Gupta</p> <p> <li>Overview of the role of artificial intelligence in pathology: the computer as a pathology digital assistant</li> </ol> <p>John E. Tomaszewski</p>