Carl Sabottke
- Radiology, Nuclear Medicine and Imaging top 10%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Signal Processing top 10%
- Co-authors
- Bradley SpielerTudor DumitraşOctavian SuciuLei ZhangDaniel A. ButtsHermann RieckeWilliam L. KathHannah Choi
- Topics
- COVID-19 diagnosis using AI (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Hepatocellular Carcinoma Treatment and Prognosis (4 papers)
- Partner nations
- United StatesCanadaSingapore
In The Last Decade
Carl Sabottke
17 papers receiving 512 citations
Peers
Comparison fields: 5 of 125
- Radiology, Nuclear Medicine and Imaging 146
- Information Systems 131
- Computer Networks and Communications 87
- Artificial Intelligence 87
- Signal Processing 71
Countries citing papers authored by Carl Sabottke
This map shows the geographic impact of Carl Sabottke'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 Carl Sabottke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carl Sabottke more than expected).
Fields of papers citing papers by Carl Sabottke
This network shows the impact of papers produced by Carl Sabottke. 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 Carl Sabottke. The network helps show where Carl Sabottke may publish in the future.
Co-authorship network of co-authors of Carl Sabottke
This figure shows the co-authorship network connecting the top 25 collaborators of Carl Sabottke. A scholar is included among the top collaborators of Carl Sabottke 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 Carl Sabottke. Carl Sabottke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 5 | |
| 3 | 15 | |
| 4 | 6 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 14 | |
| 9 | 18 | |
| 10 | 5 | |
| 11 | 23 | |
| 12 | 16 | |
| 13 | 191 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | Vulnerability disclosure in the age of social media: exploiting twitter for predicting real-world exploits | 145 |
| 17 | 69 | |
| 18 | 1 |
About Carl Sabottke
Carl Sabottke is a scholar working on Health Informatics, Hepatology and Radiology, Nuclear Medicine and Imaging, having authored 18 papers that have together received 531 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Health Informatics (34 citations), Signal Processing (71 citations) and Radiology, Nuclear Medicine and Imaging (146 citations). Carl Sabottke has collaborated with scholars based in United States, Canada and Singapore. Frequent co-authors include Bradley Spieler, Tudor Dumitraş, Octavian Suciu, Lei Zhang, Daniel A. Butts, Hermann Riecke, William L. Kath, Hannah Choi, Mark S. Cembrowski and Joshua H. Singer. Their work appears in journals such as Journal of Neuroscience, Journal of Neurophysiology and American Journal of Roentgenology.
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.