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Cited by in F6Publishing
For: De Vera Mudry MC, Martin J, Schumacher V, Venugopal R. Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy. Toxicol Pathol 2021;49:851-61. [PMID: 33371793 DOI: 10.1177/0192623320980674] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Turner OC, Knight B, Zuraw A, Litjens G, Rudmann DG. Mini Review: The Last Mile-Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology. Toxicol Pathol 2021;49:714-9. [PMID: 33590805 DOI: 10.1177/0192623321990375] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
2 Zuraw A, Aeffner F. Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review. Vet Pathol 2021;:3009858211040484. [PMID: 34521285 DOI: 10.1177/03009858211040484] [Reference Citation Analysis]
3 Mehrvar S, Himmel LE, Babburi P, Goldberg AL, Guffroy M, Janardhan K, Krempley AL, Bawa B. Deep Learning Approaches and Applications in Toxicologic Histopathology: Current Status and Future Perspectives. J Pathol Inform 2021;12:42. [PMID: 34881097 DOI: 10.4103/jpi.jpi_36_21] [Reference Citation Analysis]