Abstract
Digital pathology (DP) involves digitizing histopathology slides to generate whole slide images (WSI) and the subsequent analysis of these WSIs using various computational methods. In the 1950s McCarthy et al. coined the term “artificial intelligence (AI)” for the branch of computer science which uses machine-based approaches to arrive at certain predictions, thereby mimicking human intelligence while solving complex problems. The last decade has witnessed a promising increase in the application of AI tools in anatomic pathology. Using AI, DP can potentially revolutionize the practice of anatomic pathology as not only does it transfer an image from the glass slide to the monitor but so does it augment the pathologist’s eye with information that is impossible to be gleaned by human examination. Machine learning–based approaches are based on the machine “learning” to make predictions based on the input data and algorithms and falls within the broad ambit of AI. The applications of AI are myriad and range from objective diagnosis, quality control, cancer predication/prognostication, tumor grading, education, and research. In this chapter, we highlight the use of AI in anatomic pathology with emphasis on future directions.
Published Version
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