Abstract
There has been an exponential growth in the application of AI in health and in pathology. This is resulting in the innovation of deep learning technologies that are specifically aimed at cellular imaging and practical applications that could transform diagnostic pathology. This paper reviews the different approaches to deep learning in pathology, the public grand challenges that have driven this innovation and a range of emerging applications in pathology. The translation of AI into clinical practice will require applications to be embedded seamlessly within digital pathology workflows, driving an integrated approach to diagnostics and providing pathologists with new tools that accelerate workflow and improve diagnostic consistency and reduce errors. The clearance of digital pathology for primary diagnosis in the US by some manufacturers provides the platform on which to deliver practical AI. AI and computational pathology will continue to mature as researchers, clinicians, industry, regulatory organizations and patient advocacy groups work together to innovate and deliver new technologies to health care providers: technologies which are better, faster, cheaper, more precise, and safe.
Highlights
Artificial Intelligence (AI) along with its sub-disciplines of Machine Learning (ML) and Deep Learning (DL) are emerging as key technologies in healthcare with the potential to change lives and improve patient outcomes in many areas of medicine
The majority of efforts to date have focused on the development of neural network architectures in order to enhance the performance of different computational pathology tasks
Generative adversarial networks (GANs) are deep neural network architectures comprised of two networks, opposing one against the other (Figure 2)
Summary
Life Sciences R&D Hub, Digital and Computational Pathology, Philips, Belfast, United Kingdom. Reviewed by: Fernando Schmitt, University of Porto, Portugal Salvatore Lorenzo Renne, Humanitas Research Hospital, Italy. Specialty section: This article was submitted to Pathology, a section of the journal
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
