Applications of Digital and Computational Pathology and Artificial Intelligence in Genitourinary Pathology Diagnostics.

Journal: Surgical pathology clinics
Published Date:

Abstract

As machine learning (ML) solutions for genitourinary pathology image analysis are fostered by a progressively digitized laboratory landscape, these integrable modalities usher in a revolution in histopathological diagnosis. As technology advances, limitations stymying clinical artificial intelligence (AI) will not be extinguished without thorough validation and interrogation of ML tools by pathologists and regulatory bodies alike. ML solutions deployed in clinical settings for applications in prostate pathology yield promising results. Recent breakthroughs in clinical artificial intelligence for genitourinary pathology demonstrate unprecedented generalizability, heralding prospects for a future in which AI-driven assistive solutions may be seen as laboratory faculty, rather than novelty.

Authors

  • Ankush Uresh Patel
    Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street Southwest, Rochester, MN 55905, USA.
  • Sambit K Mohanty
    Surgical and Molecular Pathology, Advanced Medical Research Institute, Plot No. 1, Near Jayadev Vatika Park, Khandagiri, Bhubaneswar, Odisha 751019. Electronic address: https://twitter.com/SAMBITKMohanty1.
  • Anil V Parwani
    Department of Pathology, The Ohio State University Wexner Medical Centre, Columbus, OH, USA.