Nick Weiss
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 8
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- Radiomics and Machine Learning in Medical Imaging 6
- Co-authors
- Daniel Rueckert (1 shared paper)Anil Rao (1 shared paper)Johannes Lotz (7 shared papers)André Homeyer (7 shared papers)Jeroen van der Laak (4 shared papers)Rob van de Loo (2 shared papers)Geert Litjens (2 shared papers)Horst K. Hahn (3 shared papers)
- Journals
- Journal of Pathology Informatics (2 papers)Computerized Medical Imaging and Graphics (2 papers)Scientific Reports (1 paper)Frontiers in Oncology (1 paper)Disease Models & Mechanisms (1 paper)
- Partner nations
- GermanyNetherlandsSweden
In The Last Decade
Nick Weiss
16 papers receiving 347 citations
Peers
Comparison fields: 5 of 75
- Health Informatics 31
- Biophysics 53
- Radiology, Nuclear Medicine and Imaging 151
- Artificial Intelligence 176
- Computer Vision and Pattern Recognition 104
Countries citing papers authored by Nick Weiss
This map shows the geographic impact of Nick Weiss'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 Nick Weiss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nick Weiss more than expected).
Fields of papers citing papers by Nick Weiss
This network shows the impact of papers produced by Nick Weiss. 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 Nick Weiss. The network helps show where Nick Weiss may publish in the future.
Co-authors
The 25 scholars most cited alongside Nick Weiss, 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 | 2019 | 101 | |
| 2 | 2013 | 57 | |
| 3 | 2018 | 49 | |
| 4 | 2021 | 24 | |
| 5 | 2021 | 23 | |
| 6 | 2021 | 22 | |
| 7 | 2018 | 20 | |
| 8 | 2017 | 11 | |
| 9 | 2022 | 10 | |
| 10 | 2022 | 10 | |
| 11 | 2021 | 7 | |
| 12 | 2022 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2021 | 5 | |
| 15 | 2022 | 2 | |
| 16 | 2022 | 2 |
About Nick Weiss
Nick Weiss is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Health Informatics and Molecular Biology, having authored 16 papers that have together received 353 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Artificial Intelligence in Healthcare and Education (4 papers), Medical Image Segmentation Techniques (3 papers), Cancer Immunotherapy and Biomarkers (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Colorectal Cancer Treatments and Studies (1 paper) and Hepatocellular Carcinoma Treatment and Prognosis (1 paper). The work is most often cited by research in Health Informatics (31 citations), Biophysics (53 citations), Radiology, Nuclear Medicine and Imaging (151 citations), Artificial Intelligence (176 citations) and Computer Vision and Pattern Recognition (104 citations). Nick Weiss has collaborated with scholars based in Germany, Netherlands and Sweden. Frequent co-authors include Daniel Rueckert, Anil Rao, Johannes Lotz, André Homeyer, Jeroen van der Laak, Rob van de Loo, Geert Litjens, Horst K. Hahn, Christina Hulsbergen‐van de Kaa and Péter Bándi. Their work appears in journals such as Journal of Pathology Informatics, Computerized Medical Imaging and Graphics, Scientific Reports, Frontiers in Oncology and Disease Models & Mechanisms.
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.