Yoichi Yoshida

812 total citations
46 papers, 332 citations indexed

About

Yoichi Yoshida is a scholar working on Molecular Biology, Neurology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yoichi Yoshida has authored 46 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 12 papers in Neurology and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yoichi Yoshida's work include Cerebrovascular and Carotid Artery Diseases (7 papers), Intracranial Aneurysms: Treatment and Complications (5 papers) and Acute Ischemic Stroke Management (5 papers). Yoichi Yoshida is often cited by papers focused on Cerebrovascular and Carotid Artery Diseases (7 papers), Intracranial Aneurysms: Treatment and Complications (5 papers) and Acute Ischemic Stroke Management (5 papers). Yoichi Yoshida collaborates with scholars based in Japan, Iran and United States. Yoichi Yoshida's co-authors include Masayoshi Kinoshita, Kiyoshi Yamauchi, Akira Teramoto, Naoko Sanno, Shigeru Nemoto, Yasuhisa Asano, Hidenobu Komeda, Yasuo Iwadate, Yasuo Murai and Eiichi Kobayashi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Stroke and Scientific Reports.

In The Last Decade

Yoichi Yoshida

41 papers receiving 323 citations

Peers

Yoichi Yoshida

EDM

SURGE

NEURO

EPIDE

Paul K. Schick United States

John Fernandes Netherlands

Yeshitila Gebremichael United States

Cristiane Blechschmidt Germany

Satoko Sasaki Japan

Yuki Wada Japan

Xiaoting Zhu China

Weixing Hu China

Cihan Öner Türkiye

Libor Kozák Czechia

Paul K. Schick United States

Yoichi Yoshida

163 ×1.3

49 ×0.8

EDM

93 ×1.8

SURGE

58 ×1.2

NEURO

39 ×0.8

EPIDE

Citations per year, relative to Yoichi Yoshida Yoichi Yoshida (= 1×) peers Paul K. Schick

Countries citing papers authored by Yoichi Yoshida

Since Specialization

Citations

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

Fields of papers citing papers by Yoichi Yoshida

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoichi Yoshida

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

All Works

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20 of 20 papers shown

Okamoto, Takayuki, et al.. (2024). Toward an application of automatic evaluation system for central facial palsy using two simple evaluation indices in emergency medicine. Scientific Reports. 14(1). 3429–3429. 3 indexed citations

Ito, Masaaki, Satoshi Yajima, Hirotaka Takizawa, et al.. (2024). Stage-Specific Alteration and Prognostic Relationship of Serum Fumarate Hydratase Autoantibodies in Gastric Cancer. International Journal of Molecular Sciences. 25(10). 5470–5470. 1 indexed citations

Yoshida, Yoichi, Yosuke Hayashi, Tadanaga Shimada, et al.. (2023). Prehospital stroke-scale machine-learning model predicts the need for surgical intervention. Scientific Reports. 13(1). 9135–9135. 4 indexed citations

Nakamura, Rika, Yoichi Yoshida, Seiichiro Mine, et al.. (2023). GADD34 activates p53 and may have utility as a marker of atherosclerosis. Frontiers in Medicine. 10. 1128921–1128921. 3 indexed citations

Yoshida, Yoichi, et al.. (2021). Transarterial embolization for falx dural arteriovenous fistula through the artery of Davidoff and Schechter: A case report. SHILAP Revista de lepidopterología. 17(3). 700–705. 2 indexed citations

Kubota, Masaaki, Yoichi Yoshida, Eiichi Kobayashi, et al.. (2021). Serum anti-SERPINE1 antibody as a potential biomarker of acute cerebral infarction. Scientific Reports. 11(1). 21772–21772. 12 indexed citations

Hayashi, Yosuke, Tadanaga Shimada, Noriyuki Hattori, et al.. (2021). A prehospital diagnostic algorithm for strokes using machine learning: a prospective observational study. Scientific Reports. 11(1). 20519–20519. 18 indexed citations

Kubota, Masaaki, et al.. (2020). Mechanical Thrombectomy for Acute Ischemic Stroke Complicated by Bacterial Meningitis and Infective Endocarditis. Journal of Neuroendovascular Therapy. 15(3). 175–180.

Nakamura, Yoshinori, et al.. (2015). Remote Supratentorial Hemorrhage following Supratentorial Craniotomy: A Case Report. NMC Case Report Journal. 3(1). 13–15. 2 indexed citations

10.

Murai, Yasuo, Yoichi Yoshida, Takayuki Mizunari, et al.. (2011). Preoperative liquid embolization of cerebeller hemangioblastomas using N-butyl cyanoacrylate. Neuroradiology. 54(9). 981–988. 18 indexed citations

11.

Murai, Yasuo, Koji Adachi, Yoichi Yoshida, Akira Teramoto, & Takayuki Mizunari. (2010). Failure of Combined Treatment for the Thrombosed Posterior Cerebral Artery Aneurysm. Surgery for Cerebral Stroke. 38(1). 52–56. 1 indexed citations

12.

Asano, Yasuhisa, et al.. (2008). The Screening, Characterization, and Use of ω-Laurolactam Hydrolase: A New Enzymatic Synthesis of 12-Aminolauric Acid. Bioscience Biotechnology and Biochemistry. 72(8). 2141–2150. 16 indexed citations

13.

Yoshida, Yoichi, N Sanno, & Atsushi Teramoto. (2000). Multiple Pituitary Hormone Gradients from Cavernous Sinus Sampling in Patients with Cushing's Disease. Acta Neurochirurgica. 142(12). 1339–1344. 2 indexed citations

14.

Sanno, Naoko, et al.. (1999). Ectopic Corticotroph Adenoma in the Cavernous Sinus: Case Report. Neurosurgery. 45(4). 914–918. 22 indexed citations

15.

Teramoto, Akira, Yoichi Yoshida, Naoko Sanno, & Shigeru Nemoto. (1998). Cavernous sinus sampling in patients with adrenocorticotrophic hormone—dependent Cushing's syndrome with emphasis on inter- and intracavernous adrenocorticotrophic hormone gradients. Journal of neurosurgery. 89(5). 762–768. 41 indexed citations

16.

Kohno, Shigekatsu, Hideki Yamamura, Katsuya Ohata, et al.. (1988). Antiallergic effects of mequitazine. 1. In vitro experiments.. Folia Pharmacologica Japonica. 92(2). 145–157. 2 indexed citations

17.

Fujimura, Hajimè, et al.. (1981). Pharmacological study of mequitazine (LM-209) (II): anti-allergic action. Folia Pharmacologica Japonica. 78(4). 291–303. 4 indexed citations

18.

Fujimura, Hajimè, et al.. (1981). . Folia Pharmacologica Japonica. 78(4). 279–289. 3 indexed citations

19.

Yoshida, Yoichi, et al.. (1976). [Duplication of the superior caval veins--an autopsy case].. PubMed. 51(4). 251–6. 1 indexed citations

20.

Hirano, Makito, Hidenori Kawasaki, Hideaki Matsushita, & Yoichi Yoshida. (1973). [Mode of vocal cord vibration in recurrent laryngeal nerve paralysis--ultra-high speed cinematographic investigation].. PubMed. 76(6). 721–8. 1 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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