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J Nephropathol. 2021;10(3): e26. doi: 10.34172/jnp.2021.26

Original Article

The resolution of immunofluorescent pathological images affects diagnosis for not only artificial intelligence but also human

Kensaku Takahashi 1 ORCID, Shinji Kitamura 1 * ORCID, Kazuhiko Fukushima 1, Yizhen Sang 1, Kenji Tsuji 1, Jun Wada 1

Cited by CrossRef: 4

1- Fu Y, Jiang L, Pan S, Chen P, Wang X, Dai N, Chen X, Xu M. Deep multi-task learning for nephropathy diagnosis on immunofluorescence images. Computer Methods and Programs in Biomedicine. 2023;241:107747 [Crossref]
2- Magherini R, Mussi E, Volpe Y, Furferi R, Buonamici F, Servi M. Machine Learning for Renal Pathologies: An Updated Survey. Sensors. 2022;22(13):4989 [Crossref]
3- Zhuang K, Wang W, Xu C, Guo X, Ren X, Liang Y, Duan Z, Song Y, Zhang Y, Cai G. Machine learning-based diagnosis and prognosis of IgAN: A systematic review and meta-analysis. Heliyon. 2024;10(12):e33090 [Crossref]