Janani Venugopalan

1.3k total citations · 1 hit paper
22 papers, 790 citations indexed

About

Janani Venugopalan is a scholar working on Artificial Intelligence, Health Information Management and Epidemiology. According to data from OpenAlex, Janani Venugopalan has authored 22 papers receiving a total of 790 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Health Information Management and 5 papers in Epidemiology. Recurrent topics in Janani Venugopalan's work include Machine Learning in Healthcare (9 papers), Artificial Intelligence in Healthcare (4 papers) and Stroke Rehabilitation and Recovery (3 papers). Janani Venugopalan is often cited by papers focused on Machine Learning in Healthcare (9 papers), Artificial Intelligence in Healthcare (4 papers) and Stroke Rehabilitation and Recovery (3 papers). Janani Venugopalan collaborates with scholars based in United States, Russia and Cambodia. Janani Venugopalan's co-authors include May D. Wang, Hamid Reza Hassanzadeh, Tong Li, Chih‐Wen Cheng, Ryan Hoffman, Po-Yen Wu, Chanchala Kaddi, Nikhil K. Chanani, Kevin Maher and Todd H. Stokes and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and IEEE Journal of Biomedical and Health Informatics.

In The Last Decade

Janani Venugopalan

22 papers receiving 757 citations

Hit Papers

Multimodal deep learning ... 2021 2026 2022 2024 2021 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Janani Venugopalan United States 11 309 196 167 121 114 22 790
Maryam Panahiazar United States 14 347 1.1× 174 0.9× 103 0.6× 109 0.9× 142 1.2× 36 1.2k
Zhenxing Xu United States 17 320 1.0× 112 0.6× 38 0.2× 69 0.6× 100 0.9× 51 1.2k
An Zeng China 11 232 0.8× 72 0.4× 193 1.2× 131 1.1× 103 0.9× 37 650
Hager Saleh Egypt 14 373 1.2× 195 1.0× 86 0.5× 47 0.4× 123 1.1× 29 668
Dan Pan China 8 187 0.6× 69 0.4× 186 1.1× 130 1.1× 72 0.6× 28 474
Domenico Diacono Italy 14 186 0.6× 47 0.2× 104 0.6× 110 0.9× 169 1.5× 38 579
C. Kavitha India 10 164 0.5× 90 0.5× 118 0.7× 51 0.4× 71 0.6× 44 478
Vasileios C. Pezoulas Greece 13 161 0.5× 59 0.3× 58 0.3× 134 1.1× 89 0.8× 71 968

Countries citing papers authored by Janani Venugopalan

Since Specialization
Citations

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

Fields of papers citing papers by Janani Venugopalan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Janani Venugopalan

This figure shows the co-authorship network connecting the top 25 collaborators of Janani Venugopalan. A scholar is included among the top collaborators of Janani Venugopalan 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 Janani Venugopalan. Janani Venugopalan 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.
Isgut, Monica, et al.. (2022). Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era. IEEE Reviews in Biomedical Engineering. 16. 53–69. 17 indexed citations
2.
Zhu, Yuanda, et al.. (2022). Domain Adaptation Using Convolutional Autoencoder and Gradient Boosting for Adverse Events Prediction in the Intensive Care Unit. Frontiers in Artificial Intelligence. 5. 640926–640926. 6 indexed citations
3.
Venugopalan, Janani, Tong Li, Hamid Reza Hassanzadeh, & May D. Wang. (2021). Multimodal deep learning models for early detection of Alzheimer’s disease stage. Scientific Reports. 11(1). 3254–3254. 404 indexed citations breakdown →
4.
Cheng, Chih‐Wen, R. Clark Brown, Janani Venugopalan, & May D. Wang. (2019). Towards an Effective Patient Health Engagement System Using Cloud-Based Text Messaging Technology. IEEE Journal of Translational Engineering in Health and Medicine. 8. 1–7. 1 indexed citations
5.
Hoffman, Ryan, et al.. (2018). Intelligent Mortality Reporting With FHIR. IEEE Journal of Biomedical and Health Informatics. 22(5). 1583–1588. 11 indexed citations
6.
Venugopalan, Janani, Nikhil K. Chanani, Kevin Maher, & May D. Wang. (2017). Combination of static and temporal data analysis to predict mortality and readmission in the intensive care. PubMed. 2017. 2570–2573. 5 indexed citations
7.
Venugopalan, Janani, et al.. (2017). Mining standardized neurological signs and symptoms data for concussion identification. PubMed. 2017. 285–288. 1 indexed citations
8.
Hoffman, Ryan, et al.. (2017). Intelligent mortality reporting with FHIR. PubMed. 11. 181–184. 6 indexed citations
9.
Venugopalan, Janani, et al.. (2017). 11C-PIB PET image analysis for Alzheimer's diagnosis using weighted voting ensembles. PubMed. 2017. 3914–3917. 10 indexed citations
10.
Sha, Ying, Janani Venugopalan, & May D. Wang. (2016). A Novel Temporal Similarity Measure for Patients Based on Irregularly Measured Data in Electronic Health Records. PubMed. 2016. 337–344. 11 indexed citations
11.
Burns, Thomas G., et al.. (2016). Development of user-friendly and interactive data collection system for cerebral palsy. PubMed. 3. 406–409. 3 indexed citations
12.
Wu, Po-Yen, Chih‐Wen Cheng, Chanchala Kaddi, et al.. (2016). –Omic and Electronic Health Record Big Data Analytics for Precision Medicine. IEEE Transactions on Biomedical Engineering. 64(2). 263–273. 193 indexed citations
13.
Venugopalan, Janani, Chih‐Wen Cheng, & May D. Wang. (2014). MotionTalk. PubMed. 2014. 455–463. 5 indexed citations
14.
Venugopalan, Janani, et al.. (2014). Med-vest: A wearable sensory platform. PubMed. 2014. 199–202. 1 indexed citations
15.
Venugopalan, Janani, et al.. (2014). Multi-channel LED light source for fluorescent agent aided minimally invasive surgery. PubMed. 2014. 6927–6930. 2 indexed citations
16.
Stokes, Todd H., et al.. (2013). A pilot biomedical engineering course in rapid prototyping for mobile health. PubMed. 41. 2515–2518. 2 indexed citations
17.
Cheng, Chih‐Wen, R. Clark Brown, Lindsey L. Cohen, et al.. (2013). iACT - An interactive mHealth monitoring system to enhance psychotherapy for adolescents with sickle cell disease. PubMed. 2013. 2279–2282. 15 indexed citations
18.
Cheng, Chih‐Wen, Nikhil K. Chanani, Janani Venugopalan, Kevin Maher, & May D. Wang. (2013). icuARM-An ICU Clinical Decision Support System Using Association Rule Mining. IEEE Journal of Translational Engineering in Health and Medicine. 1(1). 4400110–4400110. 35 indexed citations
19.
Venugopalan, Janani, Chih‐Wen Cheng, Todd H. Stokes, & May D. Wang. (2013). Kinect-based rehabilitation system for patients with traumatic brain injury. PubMed. 2013. 4625–4628. 25 indexed citations
20.
Venugopalan, Janani, R. Clark Brown, Chih‐Wen Cheng, Todd H. Stokes, & May D. Wang. (2012). Activity and school attendance monitoring system for adolescents with Sickle cell disease. PubMed. 2012. 2456–2459. 7 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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