Madhurananda Pahar
- Pulmonary and Respiratory Medicine
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence
- Signal Processing top 10%
- Epidemiology
- Co-authors
- Thomas NieslerMarisa KlopperRobin M. WarrenAndreas H. DiaconLeslie S. SmithGrant TheronByron W P ReeveHeidi Christensen
- Topics
- Respiratory and Cough-Related Research (7 papers)Pneumonia and Respiratory Infections (5 papers)COVID-19 diagnosis using AI (5 papers)
- Journals
- Computers in Biology and MedicineIEEE Journal of Biomedical and Health InformaticsJournal of Signal Processing Systems
- Partner nations
- South AfricaUnited KingdomNetherlands
In The Last Decade
Madhurananda Pahar
12 papers receiving 319 citations
Hit Papers
Peers
Comparison fields: 5 of 57
- Pulmonary and Respiratory Medicine 190
- Radiology, Nuclear Medicine and Imaging 189
- Artificial Intelligence 84
- Signal Processing 72
- Epidemiology 47
Countries citing papers authored by Madhurananda Pahar
This map shows the geographic impact of Madhurananda Pahar'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 Madhurananda Pahar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madhurananda Pahar more than expected).
Fields of papers citing papers by Madhurananda Pahar
This network shows the impact of papers produced by Madhurananda Pahar. 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 Madhurananda Pahar. The network helps show where Madhurananda Pahar may publish in the future.
Co-authorship network of co-authors of Madhurananda Pahar
This figure shows the co-authorship network connecting the top 25 collaborators of Madhurananda Pahar. A scholar is included among the top collaborators of Madhurananda Pahar 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 Madhurananda Pahar. Madhurananda Pahar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 2 | |
| 4 | 16 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 12 | |
| 8 | Deep Transfer Learning based COVID-19 Detection in Cough, Breath and Speech using Bottleneck Features | 2 |
| 9 | COVID-19 cough classification using machine learning and global smartphone recordingsbreakdown → | 195 |
| 10 | 63 | |
| 11 | 3 | |
| 12 | 16 | |
| 13 | 9 |
About Madhurananda Pahar
Madhurananda Pahar is a scholar working on Developmental Biology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 13 papers that have together received 329 indexed citations. Recurring topics across this work include Respiratory and Cough-Related Research (7 papers), Pneumonia and Respiratory Infections (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (189 citations), Signal Processing (72 citations) and Pharmacy (32 citations). Madhurananda Pahar has collaborated with scholars based in South Africa, United Kingdom and Netherlands. Frequent co-authors include Thomas Niesler, Marisa Klopper, Robin M. Warren, Andreas H. Diacon, Leslie S. Smith, Grant Theron, Byron W P Reeve, Heidi Christensen, Gabriel Gomes de Oliveira and Daniel Braun. Their work appears in journals such as Computers in Biology and Medicine, IEEE Journal of Biomedical and Health Informatics and Journal of Signal Processing Systems.
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.