Akinori Mitani

1.4k total citations
14 papers, 544 citations indexed

About

Akinori Mitani is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Akinori Mitani has authored 14 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Cognitive Neuroscience and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Akinori Mitani's work include Neural dynamics and brain function (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Retinal Imaging and Analysis (3 papers). Akinori Mitani is often cited by papers focused on Neural dynamics and brain function (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Retinal Imaging and Analysis (3 papers). Akinori Mitani collaborates with scholars based in United States, Japan and Germany. Akinori Mitani's co-authors include Takaki Komiyama, Dale R. Webster, Greg S. Corrado, Lily Peng, Naama Hammel, Yun Liu, Avinash V. Varadarajan, Subhashini Venugopalan, Abigail E. Huang and Tadafumi Hashimoto and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Akinori Mitani

13 papers receiving 534 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Akinori Mitani United States	8	189	136	107	104	89	14	544
Tess E. Kornfield United States	5	273 1.4×	202 1.5×	72 0.7×	192 1.8×	112 1.3×	5	748
Nazanin Mirzaei United States	13	358 1.9×	154 1.1×	132 1.2×	70 0.7×	332 3.7×	23	859
Janko Dietzsch Germany	15	101 0.5×	86 0.6×	46 0.4×	39 0.4×	369 4.1×	28	678
Baolei Xu China	13	136 0.7×	93 0.7×	109 1.0×	204 2.0×	118 1.3×	41	589
Julian J. Nussbaum United States	14	80 0.4×	134 1.0×	66 0.6×	27 0.3×	252 2.8×	21	717
Mojtaba Golzan Australia	13	138 0.7×	313 2.3×	68 0.6×	16 0.2×	200 2.2×	39	742
Rustum Karanjia United States	16	161 0.9×	180 1.3×	120 1.1×	47 0.5×	379 4.3×	61	933
Pradeep Varma United States	9	294 1.6×	68 0.5×	142 1.3×	146 1.4×	99 1.1×	11	567
Jeremiah K. H. Lim Australia	13	119 0.6×	238 1.8×	71 0.7×	29 0.3×	309 3.5×	26	659
Jiajie Mo China	14	101 0.5×	128 0.9×	148 1.4×	212 2.0×	174 2.0×	66	897

Countries citing papers authored by Akinori Mitani

Since Specialization

Citations

This map shows the geographic impact of Akinori Mitani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Akinori Mitani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akinori Mitani more than expected).

Fields of papers citing papers by Akinori Mitani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akinori Mitani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Akinori Mitani. The network helps show where Akinori Mitani may publish in the future.

Co-authorship network of co-authors of Akinori Mitani

This figure shows the co-authorship network connecting the top 25 collaborators of Akinori Mitani. A scholar is included among the top collaborators of Akinori Mitani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Akinori Mitani. Akinori Mitani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Li, Eric V., Yi Ren, Rikiya Yamashita, et al.. (2025). An Artificial Intelligence–Digital Pathology Algorithm Predicts Survival After Radical Prostatectomy From the Prostate, Lung, Colorectal, and Ovarian Cancer Trial. The Journal of Urology. 213(5). 600–608.

Kreipe, Hans, Oleg Gluz, Matthias Christgen, et al.. (2024). Multimodal artificial intelligence models from baseline histopathology to predict prognosis in HR+ HER2- early breast cancer: Subgroup analysis.. Journal of Clinical Oncology. 42(16_suppl). 101–101. 2 indexed citations

Holste, Gregory, et al.. (2023). Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision. 1–5. 2 indexed citations

Feng, Felix Y., Matthew R. Smith, Fred Saad, et al.. (2023). Digital histopathology-based multimodal artificial intelligence scores predict risk of progression in a randomized phase III trial in patients with nonmetastatic castration-resistant prostate cancer.. Journal of Clinical Oncology. 41(16_suppl). 5035–5035. 1 indexed citations

Babenko, Boris, Akinori Mitani, Ilana Traynis, et al.. (2022). Detection of signs of disease in external photographs of the eyes via deep learning. Nature Biomedical Engineering. 6(12). 1370–1383. 53 indexed citations

Mitani, Akinori, et al.. (2021). Task-specific employment of sensory signals underlies rapid task switching. Cerebral Cortex. 32(21). 4657–4670. 3 indexed citations

Mitani, Akinori, Abigail E. Huang, Subhashini Venugopalan, et al.. (2020). Author Correction: Detection of anaemia from retinal fundus images via deep learning. Nature Biomedical Engineering. 4(2). 242–242. 7 indexed citations

Hwang, Eun Jung, et al.. (2019). Disengagement of motor cortex from movement control during long-term learning. Science Advances. 5(10). eaay0001–eaay0001. 54 indexed citations

Mitani, Akinori, Abigail E. Huang, Subhashini Venugopalan, et al.. (2019). Detection of anaemia from retinal fundus images via deeplearning. Nature Biomedical Engineering. 4(1). 18–27. 133 indexed citations

10.

Mitani, Akinori & Takaki Komiyama. (2018). Real-Time Processing of Two-Photon Calcium Imaging Data Including Lateral Motion Artifact Correction. Frontiers in Neuroinformatics. 12. 98–98. 34 indexed citations

11.

Mitani, Akinori, et al.. (2017). Brain-Computer Interface with Inhibitory Neurons Reveals Subtype-Specific Strategies. Current Biology. 28(1). 77–83.e4. 20 indexed citations

12.

Jacob, Vincent, Akinori Mitani, Taro Toyoizumi, & Kevin Fox. (2016). Whisker row deprivation affects the flow of sensory information through rat barrel cortex. Journal of Neurophysiology. 117(1). 4–17. 10 indexed citations

13.

Mitani, Akinori, et al.. (2013). A Leaky-Integrator Model as a Control Mechanism Underlying Flexible Decision Making during Task Switching. PLoS ONE. 8(3). e59670–e59670. 6 indexed citations

14.

Hashimoto, Tadafumi, Alberto Serrano‐Pozo, Yukiko Hori, et al.. (2012). Apolipoprotein E, Especially Apolipoprotein E4, Increases the Oligomerization of Amyloid β Peptide. Journal of Neuroscience. 32(43). 15181–15192. 219 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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