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For: Van Eycke YR, Foucart A, Decaestecker C. Strategies to Reduce the Expert Supervision Required for Deep Learning-Based Segmentation of Histopathological Images. Front Med (Lausanne) 2019;6:222. [PMID: 31681779 DOI: 10.3389/fmed.2019.00222] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 2.3] [Reference Citation Analysis]
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1 Kaczmarek-majer K, Casalino G, Castellano G, Hryniewicz O, Dominiak M. Explaining smartphone-based acoustic data in bipolar disorder: Semi-supervised fuzzy clustering and relative linguistic summaries. Information Sciences 2022;588:174-95. [DOI: 10.1016/j.ins.2021.12.049] [Reference Citation Analysis]
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5 Cornish TC. Artificial intelligence for automating the measurement of histologic image biomarkers. J Clin Invest 2021;131:147966. [PMID: 33855974 DOI: 10.1172/JCI147966] [Reference Citation Analysis]
6 Modanwal G, Vellal A, Mazurowski MA. Normalization of breast MRIs using cycle-consistent generative adversarial networks. Comput Methods Programs Biomed 2021;208:106225. [PMID: 34198016 DOI: 10.1016/j.cmpb.2021.106225] [Reference Citation Analysis]
7 Calderaro J, Kather JN. Artificial intelligence-based pathology for gastrointestinal and hepatobiliary cancers. Gut. 2020;. [PMID: 33214163 DOI: 10.1136/gutjnl-2020-322880] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]