output
20102026
most citedDevelopment and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

509 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2022★ 5 cited

Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification

Yeganeh Madadi, Vahid Seydi, Jian Sun +2

Domain adaptation is an attractive approach given the availability of a large amount of labeled data with similar properties but different domains. It is effective in image classif…

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.CV2020★ 8 cited

Automatic detection and counting of retina cell nuclei using deep learning

S. M. Hadi Hosseini, Hao Chen, Monica M. Jablonski

The ability to automatically detect, classify, calculate the size, number, and grade of retinal cells and other biological objects is critically important in eye disease like age-r…

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.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…