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For: Villoutreix P. What machine learning can do for developmental biology. Development 2021;148:dev188474. [PMID: 33431591 DOI: 10.1242/dev.188474] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Hallou A, Yevick HG, Dumitrascu B, Uhlmann V. Deep learning for bioimage analysis in developmental biology. Development 2021;148:dev199616. [PMID: 34490888 DOI: 10.1242/dev.199616] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Zhang J, Yuan T, Wei S, Feng Z, Li B, Huang H. New strategy for clinical etiologic diagnosis of acute ischemic stroke and blood biomarker discovery based on machine learning. RSC Adv 2022;12:14716-23. [PMID: 35702238 DOI: 10.1039/d2ra02022j] [Reference Citation Analysis]
3 Burggren W. Developmental Physiology: Grand Challenges. Front Physiol 2021;12:706061. [PMID: 34177630 DOI: 10.3389/fphys.2021.706061] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Driscoll MK, Zaritsky A. Data science in cell imaging. J Cell Sci 2021;134:jcs254292. [PMID: 33795377 DOI: 10.1242/jcs.254292] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
5 Naert T, Çiçek Ö, Ogar P, Bürgi M, Shaidani NI, Kaminski MM, Xu Y, Grand K, Vujanovic M, Prata D, Hildebrandt F, Brox T, Ronneberger O, Voigt FF, Helmchen F, Loffing J, Horb ME, Willsey HR, Lienkamp SS. Deep learning is widely applicable to phenotyping embryonic development and disease. Development 2021;148:dev199664. [PMID: 34739029 DOI: 10.1242/dev.199664] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]