Madhavi Raghu
- Pulmonary and Respiratory Medicine top 5%
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Oncology
- Pathology and Forensic Medicine top 10%
- Co-authors
- Jaime GeiselMelissa A. DurandLiane E. PhilpottsRegina J. HooleyBrian M. HaasVivek B. KalraLaura J. HorvathXiaopan Yao
- Topics
- Digital Radiography and Breast Imaging (7 papers)AI in cancer detection (6 papers)Breast Cancer Treatment Studies (5 papers)
- Cited by
- Pulmonary and Respiratory MedicineRadiology, Nuclear Medicine and ImagingArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterologíaRadiologyRadiographics
- Partner nations
- United StatesGermany
In The Last Decade
Madhavi Raghu
13 papers receiving 718 citations
Peers
Comparison fields: 5 of 52
- Pulmonary and Respiratory Medicine 539
- Artificial Intelligence 511
- Radiology, Nuclear Medicine and Imaging 375
- Oncology 221
- Pathology and Forensic Medicine 118
Countries citing papers authored by Madhavi Raghu
This map shows the geographic impact of Madhavi Raghu'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 Madhavi Raghu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Madhavi Raghu more than expected).
Fields of papers citing papers by Madhavi Raghu
This network shows the impact of papers produced by Madhavi Raghu. 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 Madhavi Raghu. The network helps show where Madhavi Raghu may publish in the future.
Co-authorship network of co-authors of Madhavi Raghu
This figure shows the co-authorship network connecting the top 25 collaborators of Madhavi Raghu. A scholar is included among the top collaborators of Madhavi Raghu 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 Madhavi Raghu. Madhavi Raghu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 100 | |
| 5 | 48 | |
| 6 | 86 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | 142 | |
| 10 | 323 | |
| 11 | 15 | |
| 12 | 9 | |
| 13 | Neurocutaneous melanosis with interstitial lung involvement--a rare association. | 1 |
About Madhavi Raghu
Madhavi Raghu is a scholar working on Cancer Research, Oncology and Pathology and Forensic Medicine, having authored 13 papers that have together received 740 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (7 papers), AI in cancer detection (6 papers) and Breast Cancer Treatment Studies (5 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (539 citations), Radiology, Nuclear Medicine and Imaging (375 citations) and Artificial Intelligence (511 citations). Madhavi Raghu has collaborated with scholars based in United States and Germany. Frequent co-authors include Jaime Geisel, Melissa A. Durand, Liane E. Philpotts, Regina J. Hooley, Brian M. Haas, Vivek B. Kalra, Laura J. Horvath, Xiaopan Yao, Steven Wang and Reni Butler. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiology and Radiographics.
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.