Neha Gianchandani
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Health Informatics top 2%
- Pulmonary and Respiratory Medicine
- Co-authors
- Dilbag SinghVijay KumarManjit KaurRoberto SouzaAbdollah OmidiLara M. LeijserW. Brent EdwardsAmin Komeili
- Topics
- COVID-19 diagnosis using AI (2 papers)AI in cancer detection (2 papers)Functional Brain Connectivity Studies (1 paper)
- Journals
- Scientific ReportsJournal of Biomolecular Structure and DynamicsJournal of Ambient Intelligence and Humanized Computing
- Partner nations
- CanadaIndiaUnited States
In The Last Decade
Neha Gianchandani
5 papers receiving 531 citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Radiology, Nuclear Medicine and Imaging 427
- Artificial Intelligence 317
- Computer Vision and Pattern Recognition 91
- Health Informatics 79
- Pulmonary and Respiratory Medicine 56
Countries citing papers authored by Neha Gianchandani
This map shows the geographic impact of Neha Gianchandani'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 Neha Gianchandani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neha Gianchandani more than expected).
Fields of papers citing papers by Neha Gianchandani
This network shows the impact of papers produced by Neha Gianchandani. 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 Neha Gianchandani. The network helps show where Neha Gianchandani may publish in the future.
Co-authorship network of co-authors of Neha Gianchandani
This figure shows the co-authorship network connecting the top 25 collaborators of Neha Gianchandani. A scholar is included among the top collaborators of Neha Gianchandani 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 Neha Gianchandani. Neha Gianchandani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 93 | |
| 5 | Classification of the COVID-19 infected patients using DenseNet201 based deep transfer learningbreakdown → | 437 |
About Neha Gianchandani
Neha Gianchandani is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Rheumatology, having authored 5 papers that have together received 549 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (2 papers), AI in cancer detection (2 papers) and Functional Brain Connectivity Studies (1 paper). The work is most often cited by research in Health Informatics (79 citations), Radiology, Nuclear Medicine and Imaging (427 citations) and Artificial Intelligence (317 citations). Neha Gianchandani has collaborated with scholars based in Canada, India and United States. Frequent co-authors include Dilbag Singh, Vijay Kumar, Manjit Kaur, Manjit Kaur, Roberto Souza, Abdollah Omidi, Lara M. Leijser, W. Brent Edwards, Amin Komeili and Samer Adeeb. Their work appears in journals such as Scientific Reports, Journal of Biomolecular Structure and Dynamics and Journal of Ambient Intelligence and Humanized Computing.
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.