Machine Learning Tools for Digital Pathology - The Next Big Wave in MEDICAL SCIENCE

Abstract

Digital pathology is a technology that enables the acquisition, management, and interpretation of pathological information generated from a digital slide. Glass slides are captured using digital pathology scanners and converted to digitized glass slides that can be viewed on the computer monitor. Digital pathology provides specific support for education and the practice of human pathology. With the recent advancements in digital pathology led to computer-aided diagnosis using machine learning approaches. So, machine learning tools assist physicians in diagnosing critical cases such as cancer, tumors, etc, and improve patient management. With an ever-increasing number of options, selecting a better machine learning tool for pathological data can be difficult. In this paper, huge potential efforts are made to study the complete background of digital pathology with the detail of how artificial intelligence made a contribution to digital pathology. This review also analyzes various machine learning tools by providing as much information as possible and quantifying what the tradeoffs will be. In the end, this paper provides the enhancements in available tools that will be required in the near future applications.