Hiroki Enno

739 total citations
12 papers, 482 citations indexed

About

Hiroki Enno is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Hiroki Enno has authored 12 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Ophthalmology, 8 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Biomedical Engineering. Recurrent topics in Hiroki Enno's work include Retinal Imaging and Analysis (8 papers), Retinal and Optic Conditions (5 papers) and Retinal Diseases and Treatments (5 papers). Hiroki Enno is often cited by papers focused on Retinal Imaging and Analysis (8 papers), Retinal and Optic Conditions (5 papers) and Retinal Diseases and Treatments (5 papers). Hiroki Enno collaborates with scholars based in Japan, United States and Canada. Hiroki Enno's co-authors include Hitoshi Tabuchi, Naofumi Ishitobi, Hideharu Ohsugi, Hiroki Masumoto, Yoshinori Mitamura, Daisuke Nagasato, Masanori Niki, Shunsuke Nakakura, Yoshiaki Kiuchi and Hiroki Masumoto and has published in prestigious journals such as PLoS ONE, Scientific Reports and SLEEP.

In The Last Decade

Hiroki Enno

11 papers receiving 476 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hiroki Enno Japan	10	373	342	50	47	27	12	482
Yan Tong China	10	286 0.8×	176 0.5×	23 0.5×	49 1.0×	26 1.0×	32	435
Ashutosh Richhariya India	11	351 0.9×	348 1.0×	67 1.3×	47 1.0×	10 0.4×	37	484
Sonja Karst Austria	14	320 0.9×	310 0.9×	41 0.8×	46 1.0×	17 0.6×	24	430
Sunee Chansangpetch Thailand	14	361 1.0×	407 1.2×	48 1.0×	29 0.6×	14 0.5×	56	482
Junkichi Yamagami Japan	13	487 1.3×	601 1.8×	44 0.9×	39 0.8×	15 0.6×	25	656
Jonathan D. Walker United States	7	358 1.0×	437 1.3×	13 0.3×	85 1.8×	19 0.7×	13	558
Jianyang Xie China	11	379 1.0×	279 0.8×	96 1.9×	130 2.8×	44 1.6×	31	497
Hiroki Masumoto Japan	13	361 1.0×	340 1.0×	39 0.8×	41 0.9×	25 0.9×	18	470
Jost Lennart Lauermann Germany	13	612 1.6×	585 1.7×	119 2.4×	33 0.7×	14 0.5×	29	725

Countries citing papers authored by Hiroki Enno

Since Specialization

Citations

This map shows the geographic impact of Hiroki Enno'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 Hiroki Enno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroki Enno more than expected).

Fields of papers citing papers by Hiroki Enno

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hiroki Enno. 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 Hiroki Enno. The network helps show where Hiroki Enno may publish in the future.

Co-authorship network of co-authors of Hiroki Enno

This figure shows the co-authorship network connecting the top 25 collaborators of Hiroki Enno. A scholar is included among the top collaborators of Hiroki Enno 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 Hiroki Enno. Hiroki Enno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Tsuiki, Satoru, Tatsuya Fukuda, Yuki Sakamoto, et al.. (2021). Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study. Sleep And Breathing. 25(4). 2297–2305. 26 indexed citations

Tsuiki, Satoru, Takahiro Fukuda, Yuki Sakamoto, et al.. (2020). 0594 Can a Deep Convolutional Neural Network Extract Diagnostic Information on Obstructive Sleep Apnea from Images?. SLEEP. 43(Supplement_1). A227–A227.

Masumoto, Hiroki, Hitoshi Tabuchi, Shunsuke Nakakura, et al.. (2019). Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images. PeerJ. 7. e6900–e6900. 43 indexed citations

Nagasato, Daisuke, Hitoshi Tabuchi, Hiroki Masumoto, et al.. (2019). Automated detection of a nonperfusion area caused by retinal vein occlusion in optical coherence tomography angiography images using deep learning. PLoS ONE. 14(11). e0223965–e0223965. 39 indexed citations

Nagasato, Daisuke, Hitoshi Tabuchi, Hideharu Ohsugi, et al.. (2019). Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion. International Journal of Ophthalmology. 12(1). 94–99. 46 indexed citations

Nagasato, Daisuke, Hitoshi Tabuchi, Hideharu Ohsugi, et al.. (2018). Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy. Journal of Ophthalmology. 2018. 1–6. 49 indexed citations

Tabuchi, Hitoshi, Hideharu Ohsugi, Hiroki Enno, et al.. (2018). Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration. International Ophthalmology. 39(6). 1269–1275. 72 indexed citations

Tabuchi, Hitoshi, et al.. (2018). Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT. International Ophthalmology. 39(8). 1871–1877. 37 indexed citations

Masumoto, Hiroki, et al.. (2018). Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity. Journal of Glaucoma. 27(7). 647–652. 43 indexed citations

10.

Nagasawa, Toshihiko, Hitoshi Tabuchi, Hiroki Masumoto, et al.. (2018). Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes. PeerJ. 6. e5696–e5696. 31 indexed citations

11.

Ohsugi, Hideharu, Hitoshi Tabuchi, Hiroki Enno, & Naofumi Ishitobi. (2017). Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment. Scientific Reports. 7(1). 9425–9425. 89 indexed citations

12.

Chaolumen, Chaolumen, Hiroki Enno, Michihisa Murata, Atsushi Wakamiya, & Yasujiro Murata. (2014). Dibenzo[a,f]perylene Bisimide: Effects of Introducing Two Fused Rings. Chemistry - An Asian Journal. 9(11). 3136–3140. 7 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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