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Cited by in F6Publishing
For: Yang M, Nurzynska K, Walts AE, Gertych A. A CNN-based active learning framework to identify mycobacteria in digitized Ziehl-Neelsen stained human tissues. Comput Med Imaging Graph 2020;84:101752. [PMID: 32758706 DOI: 10.1016/j.compmedimag.2020.101752] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Knyshov A, Hoang S, Weirauch C, Jockusch E. Pretrained Convolutional Neural Networks Perform Well in a Challenging Test Case: Identification of Plant Bugs (Hemiptera: Miridae) Using a Small Number of Training Images. Insect Systematics and Diversity 2021;5:3. [DOI: 10.1093/isd/ixab004] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
2 Zaizen Y, Kanahori Y, Ishijima S, Kitamura Y, Yoon H, Ozasa M, Mukae H, Bychkov A, Hoshino T, Fukuoka J. Deep-Learning-Aided Detection of Mycobacteria in Pathology Specimens Increases the Sensitivity in Early Diagnosis of Pulmonary Tuberculosis Compared with Bacteriology Tests. Diagnostics 2022;12:709. [DOI: 10.3390/diagnostics12030709] [Reference Citation Analysis]
3 Jiao Y, Li J, Fei S. Staining condition visualization in digital histopathological whole-slide images. Multimed Tools Appl. [DOI: 10.1007/s11042-022-12559-y] [Reference Citation Analysis]
4 Albert-Weiss D, Osman A. Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach. Sensors (Basel) 2022;22:414. [PMID: 35062374 DOI: 10.3390/s22020414] [Reference Citation Analysis]
5 Herman DS, Rhoads DD, Schulz WL, Durant TJS. Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review. Clin Chem 2021;67:1466-82. [PMID: 34557917 DOI: 10.1093/clinchem/hvab165] [Reference Citation Analysis]
6 Casado-García Á, Chichón G, Domínguez C, García-Domínguez M, Heras J, Inés A, López M, Mata E, Pascual V, Sáenz Y. MotilityJ: An open-source tool for the classification and segmentation of bacteria on motility images. Comput Biol Med 2021;136:104673. [PMID: 34325228 DOI: 10.1016/j.compbiomed.2021.104673] [Reference Citation Analysis]
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