Synergies and Challenges in the Preclinical and Clinical Implementation of Pathology Artificial Intelligence Applications

Abstract

Recent introduction of digitalization in pathology has disrupted the field greatly with the potential to change the area immensely. Digital pathology has created the potential of applying advanced quantitative analysis and artificial intelligence (AI) to the domain. In this study, we present an overview of what pathology AI applications have the greatest potential of widespread adoption in the preclinical domain and subsequently, in the clinical setting. We also discuss the major challenges in AI adoption being faced by the field of digital and computational pathology. We review the research literature in the domain and present a detailed analysis of the most promising areas of digital and computational pathology AI research and identify applications that are likely to see the first adoptions of AI technology. Our analysis shows that certain areas and fields of application have received more attention and can potentially affect the field of digital and computational pathology more favorably, leading to the advancement of the field. We also present the main challenges that are faced by the field and provide a comparative analysis of various aspects that are likely to influence the field for the long term in the future.