DOAJ Open Access 2023

An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

Anil V. Parwani Ankush Patel Ming Zhou John C. Cheville Hamid Tizhoosh +3 lainnya

Abstrak

Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties. This position paper provides a perspective on the evolutionary trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices. Deep learning tools for genitourinary pathology demonstrate potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation.

Topik & Kata Kunci

Computer applications to medicine. Medical informatics Pathology

Penulis (8)

Anil V. Parwani

Ankush Patel

Ming Zhou

John C. Cheville

Hamid Tizhoosh

Peter Humphrey

Victor E. Reuter

Lawrence D. True

Format Sitasi

APA MLA BibTeX

Parwani, A.V., Patel, A., Zhou, M., Cheville, J.C., Tizhoosh, H., Humphrey, P. et al. (2023). An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS). https://doi.org/10.1016/j.jpi.2022.100177

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1016/j.jpi.2022.100177
Akses: Open Access ✓