Chandrakanth Jayachandran Preetha
- Radiology, Nuclear Medicine and Imaging
- Genetics
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Pulmonary and Respiratory Medicine
- Co-authors
- Michael WellerGianluca BrugnaraMartha FoltynFabian IsenseeJean‐Sébastien FrenelJaap C. ReijneveldAlba A. BrandesDeepak Mishra
- Topics
- Radiomics and Machine Learning in Medical Imaging (2 papers)Glioma Diagnosis and Treatment (2 papers)Medical Imaging and Analysis (1 paper)
- Journals
- Radiology Artificial IntelligenceNeuro-Oncology PracticeZurich Open Repository and Archive (University of Zurich)
- Partner nations
- GermanySwitzerlandNetherlands
In The Last Decade
Chandrakanth Jayachandran Preetha
5 papers receiving 56 citations
Peers
Comparison fields: 5 of 25
- Radiology, Nuclear Medicine and Imaging 40
- Genetics 23
- Artificial Intelligence 12
- Computer Vision and Pattern Recognition 10
- Pulmonary and Respiratory Medicine 8
Countries citing papers authored by Chandrakanth Jayachandran Preetha
This map shows the geographic impact of Chandrakanth Jayachandran Preetha'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 Chandrakanth Jayachandran Preetha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chandrakanth Jayachandran Preetha more than expected).
Fields of papers citing papers by Chandrakanth Jayachandran Preetha
This network shows the impact of papers produced by Chandrakanth Jayachandran Preetha. 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 Chandrakanth Jayachandran Preetha. The network helps show where Chandrakanth Jayachandran Preetha may publish in the future.
Co-authorship network of co-authors of Chandrakanth Jayachandran Preetha
This figure shows the co-authorship network connecting the top 25 collaborators of Chandrakanth Jayachandran Preetha. A scholar is included among the top collaborators of Chandrakanth Jayachandran Preetha 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 Chandrakanth Jayachandran Preetha. Chandrakanth Jayachandran Preetha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 8 | |
| 4 | 38 | |
| 5 | 2 |
About Chandrakanth Jayachandran Preetha
Chandrakanth Jayachandran Preetha is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 5 papers that have together received 56 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Glioma Diagnosis and Treatment (2 papers) and Medical Imaging and Analysis (1 paper). The work is most often cited by research in Health Informatics (8 citations), Genetics (23 citations) and Radiology, Nuclear Medicine and Imaging (40 citations). Chandrakanth Jayachandran Preetha has collaborated with scholars based in Germany, Switzerland and Netherlands. Frequent co-authors include Michael Weller, Gianluca Brugnara, Martha Foltyn, Fabian Isensee, Jean‐Sébastien Frenel, Jaap C. Reijneveld, Alba A. Brandes, Deepak Mishra, Martin Bendszus and Martin Klein. Their work appears in journals such as Radiology Artificial Intelligence, Neuro-Oncology Practice and Zurich Open Repository and Archive (University of Zurich).
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.