All India Institute of Ayurveda, New Delhi
Impact in
-
- Traditional Chinese Medicine Studies
- Phytochemicals and Medicinal Plants
- Complementary and Alternative Medicine Studies
- Medicinal Plants and Neuroprotection
Papers in
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- Traditional Chinese Medicine Studies 259
- Phytochemicals and Medicinal Plants 62
- Complementary and Alternative Medicine Studies 44
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- Artificial Intelligence in Healthcare and Education 9
- Top scholars
- Pradeep kumar PrajapatiRohit SharmaAtul KabraTanuja Manoj NesariDeepika KanyalKamil KučaAshun ChaudharyNatália Alves Martins
- Journals
- Journal of Ayurveda and Integrative Medicine (30 papers)Scientific Reports (2 papers)Computers in Biology and Medicine (2 papers)BMJ Open (2 papers)Indian Journal of Pharmaceutical Sciences (2 papers)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
All India Institute of Ayurveda, New Delhi
306 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 141
- Complementary and alternative medicine 635
- Drug Discovery 5
- Health Informatics 27
- Infectious Diseases 141
- Plant Science 234
Countries citing scholars working at All India Institute of Ayurveda, New Delhi
This map shows the geographic impact of research produced by authors working at All India Institute of Ayurveda, New Delhi. 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 papers produced at All India Institute of Ayurveda, New Delhi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites All India Institute of Ayurveda, New Delhi more than expected).
Fields of papers published by authors at All India Institute of Ayurveda, New Delhi
This network shows the impact of papers affiliated with All India Institute of Ayurveda, New Delhi at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with All India Institute of Ayurveda, New Delhi at the time of their publication.
About All India Institute of Ayurveda, New Delhi
In recent decades, authors affiliated with All India Institute of Ayurveda, New Delhi have published 462 papers, which have received a total of 1.6k indexed citations . Scholars at this organization have produced 316 papers in Complementary and alternative medicine, 9 papers in Health Informatics, 9 papers in Toxicology, 15 papers in Analytical Chemistry and 10 papers in Pharmacology on the topics of Traditional Chinese Medicine Studies (259 papers), Phytochemicals and Medicinal Plants (62 papers), Complementary and Alternative Medicine Studies (44 papers), Medicinal Plant Research (26 papers), COVID-19 Clinical Research Studies (11 papers), Analytical Methods in Pharmaceuticals (10 papers), Natural Antidiabetic Agents Studies (9 papers) and Artificial Intelligence in Healthcare and Education (9 papers). Their work is cited by papers focused on Complementary and alternative medicine (635 citations), Drug Discovery (5 citations), Health Informatics (27 citations), Infectious Diseases (141 citations) and Plant Science (234 citations). Authors at All India Institute of Ayurveda, New Delhi collaborate with scholars in India, United States and Germany and have published in prestigious journals including Journal of Ayurveda and Integrative Medicine, Scientific Reports, Computers in Biology and Medicine, BMJ Open and Indian Journal of Pharmaceutical Sciences. Some of All India Institute of Ayurveda, New Delhi's most productive authors include Pradeep kumar Prajapati, Rohit Sharma, Atul Kabra, Tanuja Manoj Nesari, Deepika Kanyal, Kamil Kuča, Ashun Chaudhary, Natália Alves Martins, Vineet Sharma and Eugenie Nepovimová.
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.