output
20162024
most citedDevelopment and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

509 citations

Showing cs.CVShow all

5 papers · 1 filter

cs.CV2020★ 50 cited

Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading

Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20

Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…

cs.CV2019★ 127 cited

Similar Image Search for Histopathology: SMILY

Narayan Hegde, Jason D. Hipp, Yun Liu +11

The increasing availability of large institutional and public histopathology image datasets is enabling the searching of these datasets for diagnosis, research, and education. Thou…

cs.CV2019★ 101 cited

Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection

Timo Kohlberger, Yun Liu, Melissa Moran +6

Digital pathology enables remote access or consults and powerful image analysis algorithms. However, the slide digitization process can create artifacts such as out-of-focus (OOF).…

cs.CV2018★ 347 cited

Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration

Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald +7

The brightfield microscope is instrumental in the visual examination of both biological and physical samples at sub-millimeter scales. One key clinical application has been in canc…

cs.CV2018★ 509 cited

Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

Kunal Nagpal, Davis Foote, Yun Liu +17

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scorin…