Nicholas Konz
Impact in
- Health Informatics top 10%
-
- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
Papers in
-
- Generative Adversarial Networks and Image Synthesis 2
- Medical Image Segmentation Techniques 2
-
- AI in cancer detection 5
- Anomaly Detection Techniques and Applications 2
- Natural Language Processing Techniques 1
- Co-authors
- Maciej A. Mazurowski (8 shared papers)Haoyu Dong (6 shared papers)Hanxue Gu (5 shared papers)Jichen Yang (1 shared paper)Yixin Zhang (1 shared paper)Longfei Zhou (1 shared paper)Zhang Li (1 shared paper)Mateusz Buda (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (2 papers)Medical Image Analysis (2 papers)Scientific Reports (1 paper)Journal of Digital Imaging (1 paper)IEEE Transactions on Systems Man and Cybernetics Systems (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Nicholas Konz
8 papers receiving 461 citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Health Informatics 15
- Computer Vision and Pattern Recognition 180
- Radiology, Nuclear Medicine and Imaging 135
- Industrial and Manufacturing Engineering 51
- Neurology 41
Countries citing papers authored by Nicholas Konz
This map shows the geographic impact of Nicholas Konz'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 Nicholas Konz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Konz more than expected).
Fields of papers citing papers by Nicholas Konz
This network shows the impact of papers produced by Nicholas Konz. 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 Nicholas Konz. The network helps show where Nicholas Konz may publish in the future.
Co-authors
The 13 scholars most cited alongside Nicholas Konz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Segment anything model for medical image analysis: An experimental study Hit paper breakdown → | 2023 | 342 |
| 2 | 2022 | 99 | |
| 3 | 2021 | 14 | |
| 4 | 2023 | 7 | |
| 5 | 2022 | 6 | |
| 6 | 2023 | 2 | |
| 7 | 2018 | 2 | |
| 8 | 2025 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2024 | 0 |
About Nicholas Konz
Nicholas Konz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Statistical and Nonlinear Physics and Neurology, having authored 11 papers that have together received 474 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), COVID-19 diagnosis using AI (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Medical Image Segmentation Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Natural Language Processing Techniques (1 paper), Cell Image Analysis Techniques (1 paper) and Mechanics and Biomechanics Studies (1 paper). The work is most often cited by research in Health Informatics (15 citations), Computer Vision and Pattern Recognition (180 citations), Radiology, Nuclear Medicine and Imaging (135 citations), Industrial and Manufacturing Engineering (51 citations) and Neurology (41 citations). Nicholas Konz has collaborated with scholars based in United States and China. Frequent co-authors include Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Yixin Zhang, Longfei Zhou, Zhang Li, Mateusz Buda, James S. Duncan and Lin Li. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis, Scientific Reports, Journal of Digital Imaging and IEEE Transactions on Systems Man and Cybernetics 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.