Tomohiko Ai

3.4k total citations
77 papers, 1.8k citations indexed

About

Tomohiko Ai is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Tomohiko Ai has authored 77 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Cardiology and Cardiovascular Medicine, 36 papers in Molecular Biology and 12 papers in Infectious Diseases. Recurrent topics in Tomohiko Ai's work include Cardiac electrophysiology and arrhythmias (31 papers), Ion channel regulation and function (28 papers) and Cardiac Arrhythmias and Treatments (12 papers). Tomohiko Ai is often cited by papers focused on Cardiac electrophysiology and arrhythmias (31 papers), Ion channel regulation and function (28 papers) and Cardiac Arrhythmias and Treatments (12 papers). Tomohiko Ai collaborates with scholars based in Japan, United States and China. Tomohiko Ai's co-authors include Minoru Horie, Hideo Otani, Peng‐Sheng Chen, Isik Turker, Zhenhui Chen, Wataru Shimizu, Jie Cheng, Po‐Cheng Chang, Shiro Kamakura and James N. Weiss and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Tomohiko Ai

74 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomohiko Ai Japan 21 1.2k 1.0k 167 136 82 77 1.8k
Rishi Arora United States 30 2.3k 1.9× 364 0.4× 92 0.6× 51 0.4× 126 1.5× 94 2.9k
Haiyan Jin China 22 241 0.2× 519 0.5× 77 0.5× 95 0.7× 102 1.2× 59 1.3k
Emily J. Tsai United States 15 568 0.5× 782 0.8× 79 0.5× 97 0.7× 187 2.3× 27 1.6k
Mandar A. Aras United States 13 493 0.4× 241 0.2× 149 0.9× 158 1.2× 23 0.3× 34 1.2k
Christian F. Krebs Germany 28 309 0.2× 529 0.5× 28 0.2× 161 1.2× 46 0.6× 72 2.4k
Shikha Mishra United States 18 424 0.3× 1.0k 1.0× 101 0.6× 40 0.3× 23 0.3× 45 1.4k
Fu Siong Ng United Kingdom 25 1.5k 1.2× 402 0.4× 126 0.8× 51 0.4× 12 0.1× 168 2.1k
Gerold Mönnig Germany 27 2.0k 1.6× 764 0.7× 86 0.5× 89 0.7× 25 0.3× 95 2.3k
Tim Seidler Germany 28 1.2k 0.9× 804 0.8× 127 0.8× 135 1.0× 11 0.1× 61 1.8k

Countries citing papers authored by Tomohiko Ai

Since Specialization
Citations

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

Fields of papers citing papers by Tomohiko Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomohiko Ai

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

All Works

20 of 20 papers shown
1.
Zhang, Sheng, et al.. (2025). Development of a machine learning-driven formula for calculating fragment velocity. International Journal of Impact Engineering. 201. 105288–105288.
3.
Ai, Tomohiko, Takamasa Yamamoto, Shuko Nojiri, et al.. (2022). Antibody response and seroprevalence in healthcare workers after the BNT162b2 vaccination in a University Hospital at Tokyo. Scientific Reports. 12(1). 8707–8707. 10 indexed citations
4.
Ohno, Seiko, Qi Wang, Megumi Fukuyama, et al.. (2022). Increased CaV1.2 late current by a CACNA1C p.R412M variant causes an atypical Timothy syndrome without syndactyly. Scientific Reports. 12(1). 18984–18984. 1 indexed citations
5.
Hiki, Makoto, Yoko Tabe, Tomohiko Ai, et al.. (2021). Seroprevalence of anti-SARS-CoV-2 antibodies in Japanese COVID-19 patients. PLoS ONE. 16(4). e0249449–e0249449. 7 indexed citations
6.
Yamamoto, Takamasa, et al.. (2021). Clinical Evaluation of Siemens SARS-CoV-2 Total Antibody assay and IgG assay using the Dimension EXL 200 in the Tokyo Metropolitan area. Heliyon. 7(11). e08393–e08393. 4 indexed citations
7.
Ai, Tomohiko, et al.. (2020). Laceration of the transverse mesocolon in an old man with a habit of abdominal massage for constipation: a case report. SHILAP Revista de lepidopterología. 6(1). 1–1. 11 indexed citations
8.
Hirayama, Satoshi, Masahiro Tamura, Tsuyoshi Ueno, et al.. (2019). Hemolysis Is Responsible for Elevation of Serum Iron Concentration After Regular Exercises in Judo Athletes. Biological Trace Element Research. 197(1). 63–69. 14 indexed citations
9.
Tabe, Yoko, et al.. (2019). A Novel Automated Image Analysis System Using Deep Convolutional Neural Networks to Diagnose MDS. Blood. 134(Supplement_1). 4670–4670. 2 indexed citations
10.
11.
Takemura, Hiroyuki, Tomohiko Ai, Toshihiro Takahashi, et al.. (2018). Evaluation of cell count and classification capabilities in body fluids using a fully automated Sysmex XN equipped with high-sensitive Analysis (hsA) mode and DI-60 hematology analyzer system. PLoS ONE. 13(4). e0195923–e0195923. 14 indexed citations
13.
Turker, Isik, Chih‐Chieh Yu, Zhenhui Chen, et al.. (2013). Amiodarone Inhibits Apamin-Sensitive Potassium Currents. PLoS ONE. 8(7). e70450–e70450. 25 indexed citations
14.
Yang, Donghui, Yutao Xi, Tomohiko Ai, et al.. (2011). Vagal Stimulation Promotes Atrial Electrical Remodeling Induced by Rapid Atrial Pacing in Dogs: Evidence of a Noncholinergic Effect. Pacing and Clinical Electrophysiology. 34(9). 1092–1099. 20 indexed citations
15.
Itoh, Hideki, Wataru Shimizu, Kenshi Hayashi, et al.. (2010). Long QT syndrome with compound mutations is associated with a more severe phenotype: A Japanese multicenter study. Heart Rhythm. 7(10). 1411–1418. 87 indexed citations
16.
Ai, Tomohiko, Jeffrey A. Towbin, Ramón Brugada, et al.. (2009). A Nonsense SCN5A Mutation Associated with Brugada‐Type Electrocardiogram and Intraventricular Conduction Defects. Pacing and Clinical Electrophysiology. 32(9). 1231–1236. 6 indexed citations
17.
Wu, Geru, Tomohiko Ai, Jeffrey J. Kim, et al.. (2008). α-1-Syntrophin Mutation and the Long-QT Syndrome. Circulation Arrhythmia and Electrophysiology. 1(3). 193–201. 85 indexed citations
18.
Ai, Tomohiko, Silvia G. Bompadre, Xiaohui Wang, et al.. (2004). Capsaicin Potentiates Wild-Type and Mutant Cystic Fibrosis Transmembrane Conductance Regulator Chloride-Channel Currents. Molecular Pharmacology. 65(6). 1415–1426. 54 indexed citations
19.
Ai, Tomohiko, Silvia G. Bompadre, Yoshiro Sohma, et al.. (2004). Direct effects of 9-anthracene compounds on cystic fibrosis transmembrane conductance regulator gating. Pflügers Archiv - European Journal of Physiology. 449(1). 88–95. 14 indexed citations
20.
Ai, Tomohiko, et al.. (1998). Accentuated antagonism by angiotensin II on guinea-pig cardiac L-type Ca-currents enhanced by β-adrenergic stimulation. Pflügers Archiv - European Journal of Physiology. 436(2). 168–174. 20 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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