Ai Dozen

739 total citations
12 papers, 483 citations indexed

About

Ai Dozen is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Ai Dozen has authored 12 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Molecular Biology and 3 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Ai Dozen's work include Fetal and Pediatric Neurological Disorders (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Ovarian cancer diagnosis and treatment (3 papers). Ai Dozen is often cited by papers focused on Fetal and Pediatric Neurological Disorders (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Ovarian cancer diagnosis and treatment (3 papers). Ai Dozen collaborates with scholars based in Japan, United Kingdom and United States. Ai Dozen's co-authors include Kanto Shozu, Ken Asada, Masaaki Komatsu, Hidenori Machino, Ryuji Hamamoto, Syuzo Kaneko, Akira Sakai, Suguru Yasutomi, Tatsuya Arakaki and Akihiko Sekizawa and has published in prestigious journals such as Cancers, Applied Sciences and Experimental & Molecular Medicine.

In The Last Decade

Ai Dozen

12 papers receiving 469 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ai Dozen Japan	10	203	134	115	80	79	12	483
Kanto Shozu Japan	10	203 1.0×	134 1.0×	115 1.0×	81 1.0×	79 1.0×	12	484
Suguru Yasutomi Japan	8	147 0.7×	83 0.6×	82 0.7×	43 0.5×	85 1.1×	18	347
Hidenori Machino Japan	15	263 1.3×	172 1.3×	134 1.2×	174 2.2×	81 1.0×	25	719
Yinhui Deng China	10	174 0.9×	44 0.3×	28 0.2×	61 0.8×	67 0.8×	19	457
Margaret Pain United States	15	203 1.0×	147 1.1×	134 1.2×	111 1.4×	14 0.2×	31	800
Mircea-Sebastian Şerbănescu Romania	10	118 0.6×	134 1.0×	20 0.2×	59 0.7×	29 0.4×	90	422
Mohamed Shehata Egypt	14	377 1.9×	152 1.1×	61 0.5×	36 0.5×	67 0.8×	55	648
Yijie Dong China	16	447 2.2×	142 1.1×	41 0.4×	71 0.9×	5 0.1×	52	734
Ge-Ge Wu China	9	479 2.4×	318 2.4×	103 0.9×	31 0.4×	4 0.1×	10	710
Nathaniel Swinburne United States	10	223 1.1×	113 0.8×	108 0.9×	19 0.2×	14 0.2×	18	512

Countries citing papers authored by Ai Dozen

Since Specialization

Citations

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

Fields of papers citing papers by Ai Dozen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ai Dozen

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

Machino, Hidenori, Ai Dozen, Masaaki Komatsu, et al.. (2023). Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas. Experimental & Molecular Medicine. 55(10). 2205–2219. 6 indexed citations

Shozu, Kanto, Syuzo Kaneko, Norio Shinkai, et al.. (2022). Repression of the PRELP gene is relieved by histone deacetylase inhibitors through acetylation of histone H2B lysine 5 in bladder cancer. Clinical Epigenetics. 14(1). 147–147. 9 indexed citations

Machino, Hidenori, Syuzo Kaneko, Masaaki Komatsu, et al.. (2022). The metabolic stress-activated checkpoint LKB1-MARK3 axis acts as a tumor suppressor in high-grade serous ovarian carcinoma. Communications Biology. 5(1). 39–39. 17 indexed citations

Dozen, Ai, Kanto Shozu, Norio Shinkai, et al.. (2022). Tumor Suppressive Role of the PRELP Gene in Ovarian Clear Cell Carcinoma. Journal of Personalized Medicine. 12(12). 1999–1999. 11 indexed citations

Sakai, Akira, Masaaki Komatsu, Ryu Matsuoka, et al.. (2022). Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening. Biomedicines. 10(3). 551–551. 32 indexed citations

Komatsu, Masaaki, Akira Sakai, Ai Dozen, et al.. (2021). Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging. Biomedicines. 9(7). 720–720. 75 indexed citations

Yasutomi, Suguru, Tatsuya Arakaki, Ryu Matsuoka, et al.. (2021). Shadow Estimation for Ultrasound Images Using Auto-Encoding Structures and Synthetic Shadows. Applied Sciences. 11(3). 1127–1127. 24 indexed citations

Komatsu, Masaaki, Akira Sakai, Ryu Matsuoka, et al.. (2021). Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning. Applied Sciences. 11(1). 371–371. 87 indexed citations

Shozu, Kanto, Masaaki Komatsu, Akira Sakai, et al.. (2020). Model-Agnostic Method for Thoracic Wall Segmentation in Fetal Ultrasound Videos. Biomolecules. 10(12). 1691–1691. 34 indexed citations

10.

Dozen, Ai, Masaaki Komatsu, Akira Sakai, et al.. (2020). Image Segmentation of the Ventricular Septum in Fetal Cardiac Ultrasound Videos Based on Deep Learning Using Time-Series Information. Biomolecules. 10(11). 1526–1526. 60 indexed citations

11.

Hamamoto, Ryuji, Kruthi Suvarna, Masayoshi Yamada, et al.. (2020). Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine. Cancers. 12(12). 3532–3532. 126 indexed citations

12.

Nomura, Hiroyuki, Ai Dozen, S. Hashimoto, et al.. (2020). A prospective cohort study on the safety and efficacy of bevacizumab combined with chemotherapy in Japanese patients with relapsed ovarian, fallopian tube or primary peritoneal cancer. Japanese Journal of Clinical Oncology. 51(1). 54–59. 2 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.

Explore authors with similar magnitude of impact