Predrag R. Bakić
- Radiology, Nuclear Medicine and Imaging top 1%
- Pulmonary and Respiratory Medicine top 2%
- Artificial Intelligence top 2%
- Biomedical Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Andrew D. A. MaidmentMichael AlbertD. BrzakovićDavid D. PokrajacDespina KontosBruno BarufaldiCuiping ZhangAndrea B. Troxel
- Topics
- Digital Radiography and Breast Imaging (110 papers)AI in cancer detection (75 papers)Medical Imaging Techniques and Applications (74 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingPulmonary and Respiratory MedicineArtificial Intelligence
- Partner nations
- United StatesSwedenBrazil
In The Last Decade
Predrag R. Bakić
141 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 87
- Radiology, Nuclear Medicine and Imaging 1.3k
- Pulmonary and Respiratory Medicine 1.2k
- Artificial Intelligence 772
- Biomedical Engineering 508
- Computer Vision and Pattern Recognition 238
Countries citing papers authored by Predrag R. Bakić
This map shows the geographic impact of Predrag R. Bakić'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 Predrag R. Bakić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Predrag R. Bakić more than expected).
Fields of papers citing papers by Predrag R. Bakić
This network shows the impact of papers produced by Predrag R. Bakić. 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 Predrag R. Bakić. The network helps show where Predrag R. Bakić may publish in the future.
Co-authorship network of co-authors of Predrag R. Bakić
This figure shows the co-authorship network connecting the top 25 collaborators of Predrag R. Bakić. A scholar is included among the top collaborators of Predrag R. Bakić 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 Predrag R. Bakić. Predrag R. Bakić 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | Simulation and evaluation of clinically relevant features in a computational skin model | 1 |
| 8 | 2 | |
| 9 | 14 | |
| 10 | Investigating poisson noise filtering in Digital Breast Tomosynthesis | 1 |
| 11 | 6 | |
| 12 | 39 | |
| 13 | 55 | |
| 14 | 84 | |
| 15 | AUTOMATIC DETECTION OF REGION OF INTERESTS IN MAMMOGRAPHIC IMAGES | 1 |
| 16 | 19 | |
| 17 | 15 | |
| 18 | 47 | |
| 19 | 16 | |
| 20 | 68 |
About Predrag R. Bakić
Predrag R. Bakić is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 157 papers that have together received 1.7k indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (110 papers), AI in cancer detection (75 papers) and Medical Imaging Techniques and Applications (74 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.3k citations), Pulmonary and Respiratory Medicine (1.2k citations) and Artificial Intelligence (772 citations). Predrag R. Bakić has collaborated with scholars based in United States, Sweden and Brazil. Frequent co-authors include Andrew D. A. Maidment, Michael Albert, D. Brzaković, David D. Pokrajac, Despina Kontos, Bruno Barufaldi, Cuiping Zhang, Andrea B. Troxel, Kyle J. Myers and Subok Park. Their work appears in journals such as Current Biology, Radiology and Expert Systems with Applications.
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.