Anu Venkatesh
Impact in
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis
- Artificial Intelligence top 10%
- Topic Modeling
- Speech and dialogue systems
- Natural Language Processing Techniques
- AI in Service Interactions
Papers in
-
- Topic Modeling 3
- Speech and dialogue systems 2
- AI in Service Interactions 2
-
- Liver physiology and pathology 1
- Co-authors
- Yujin Hoshida (6 shared papers)Raefer Gabriel (3 shared papers)Behnam Hedayatnia (3 shared papers)Shigeki Nakagawa (4 shared papers)Anna Gottardi (1 shared paper)Dilek Hakkani‐Tür (1 shared paper)Karthik Gopalakrishnan (1 shared paper)C. Billie Bian (1 shared paper)
- Journals
- Biochemical and Biophysical Research Communications (1 paper)Experimental & Molecular Medicine (1 paper)AI Magazine (1 paper)PLoS ONE (1 paper)Bioorganic & Medicinal Chemistry Letters (1 paper)
- Partner nations
- United StatesJapanSwitzerland
In The Last Decade
Anu Venkatesh
9 papers receiving 572 citations
Peers
Comparison fields: 5 of 87
- Hepatology 81
- Artificial Intelligence 170
- Health Informatics 6
- Oncology 107
- Cancer Research 59
Countries citing papers authored by Anu Venkatesh
This map shows the geographic impact of Anu Venkatesh'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 Anu Venkatesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anu Venkatesh more than expected).
Fields of papers citing papers by Anu Venkatesh
This network shows the impact of papers produced by Anu Venkatesh. 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 Anu Venkatesh. The network helps show where Anu Venkatesh may publish in the future.
Co-authors
The 25 scholars most cited alongside Anu Venkatesh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 216 | |
| 2 | 2019 | 129 | |
| 3 | 2015 | 66 | |
| 4 | 2017 | 62 | |
| 5 | 2014 | 40 | |
| 6 | 2018 | 38 | |
| 7 | On Evaluating and Comparing Conversational Agents | 2018 | 24 |
| 8 | 2016 | 6 | |
| 9 | 2014 | 3 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 |
About Anu Venkatesh
Anu Venkatesh is a scholar working on Artificial Intelligence, Hepatology, Molecular Biology, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 584 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Cancer Mechanisms and Therapy (2 papers), Speech and dialogue systems (2 papers), AI in Service Interactions (2 papers), PARP inhibition in cancer therapy (1 paper), Prostate Cancer Treatment and Research (1 paper), Wikis in Education and Collaboration (1 paper) and Liver physiology and pathology (1 paper). The work is most often cited by research in Hepatology (81 citations), Artificial Intelligence (170 citations), Health Informatics (6 citations), Oncology (107 citations) and Cancer Research (59 citations). Anu Venkatesh has collaborated with scholars based in United States, Japan and Switzerland. Frequent co-authors include Yujin Hoshida, Raefer Gabriel, Behnam Hedayatnia, Shigeki Nakagawa, Anna Gottardi, Dilek Hakkani‐Tür, Karthik Gopalakrishnan, C. Billie Bian, Marina Ruiz de Galarreta and Verónica Miguela. Their work appears in journals such as Biochemical and Biophysical Research Communications, Experimental & Molecular Medicine, AI Magazine, PLoS ONE and Bioorganic & Medicinal Chemistry Letters.
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.