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Daniel G. Rudmann

Charles River Laboratories

6

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33

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Mini Review: The Last Mile-Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology.

2021 Toxicologic Pathology
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Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies.

2020 Toxicologic Pathology
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Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.

2020 Toxicologic Pathology
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Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology:

2019 Toxicologic Pathology
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Response to Letter to the Editor Regarding “Interstitial Adipocytes in the Beagle Dog and New Zealand White Rabbit Choroid Plexus”:

2019 Toxicologic Pathology
- Daniel G. Rudmann
- Curtis Colleton
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