Chaitanya Shivade
- Artificial Intelligence top 2%
- Molecular Biology
- Health Information Management top 1%
- Epidemiology
- Health Informatics top 2%
- Co-authors
- Albert M. LaiEric Fosler‐LussierAlexey RomanovPeter J. EmbíNoémie ElhadadPreethi RaghavanStephen B. JohnsonAsma Ben Abacha
- Topics
- Biomedical Text Mining and Ontologies (11 papers)Topic Modeling (11 papers)Natural Language Processing Techniques (7 papers)
- Journals
- Journal of the American Medical Informatics AssociationJournal of Biomedical InformaticsBMC Medical Informatics and Decision Making
- Partner nations
- United StatesChileGermany
In The Last Decade
Chaitanya Shivade
20 papers receiving 775 citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 588
- Molecular Biology 297
- Health Information Management 141
- Epidemiology 76
- Health Informatics 54
Countries citing papers authored by Chaitanya Shivade
This map shows the geographic impact of Chaitanya Shivade'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 Chaitanya Shivade with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaitanya Shivade more than expected).
Fields of papers citing papers by Chaitanya Shivade
This network shows the impact of papers produced by Chaitanya Shivade. 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 Chaitanya Shivade. The network helps show where Chaitanya Shivade may publish in the future.
Co-authorship network of co-authors of Chaitanya Shivade
This figure shows the co-authorship network connecting the top 25 collaborators of Chaitanya Shivade. A scholar is included among the top collaborators of Chaitanya Shivade 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 Chaitanya Shivade. Chaitanya Shivade is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 44 | |
| 2 | 7 | |
| 3 | 21 | |
| 4 | 1 | |
| 5 | Why Conversational AI won’t replace healthcare providers | 2 |
| 6 | 69 | |
| 7 | 119 | |
| 8 | A Quantitative and Qualitative Evaluation of Sentence Boundary Detection for the Clinical Domain. | 21 |
| 9 | 6 | |
| 10 | Automatic data source identification for clinical trial eligibility criteria resolution. | 7 |
| 11 | 22 | |
| 12 | 33 | |
| 13 | 6 | |
| 14 | 5 | |
| 15 | 46 | |
| 16 | 2 | |
| 17 | 349 | |
| 18 | 10 | |
| 19 | 46 | |
| 20 | 1 |
About Chaitanya Shivade
Chaitanya Shivade is a scholar working on Health Informatics, Family Practice and Artificial Intelligence, having authored 20 papers that have together received 817 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (11 papers), Topic Modeling (11 papers) and Natural Language Processing Techniques (7 papers). The work is most often cited by research in Health Informatics (54 citations), Health Information Management (141 citations) and Artificial Intelligence (588 citations). Chaitanya Shivade has collaborated with scholars based in United States, Chile and Germany. Frequent co-authors include Albert M. Lai, Eric Fosler‐Lussier, Alexey Romanov, Peter J. Embí, Noémie Elhadad, Preethi Raghavan, Stephen B. Johnson, Asma Ben Abacha, Dina Demner‐Fushman and Courtney Hebert. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics and BMC Medical Informatics and Decision Making.
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.