Nick Pawlowski
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Electrical and Electronic Engineering
- Co-authors
- Ben GlockerNat DilokthanakulKersten PetersenMichiel SchaapMurray ShanahanMartin RajchlDaniel RueckertIoannis Lavdas
- Topics
- Medical Image Segmentation Techniques (2 papers)AI in cancer detection (2 papers)Brain Tumor Detection and Classification (2 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Medical ImagingIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- United KingdomSwitzerlandUnited States
In The Last Decade
Nick Pawlowski
11 papers receiving 291 citations
Peers
Comparison fields: 5 of 72
- Radiology, Nuclear Medicine and Imaging 127
- Artificial Intelligence 122
- Computer Vision and Pattern Recognition 93
- Biomedical Engineering 46
- Electrical and Electronic Engineering 32
Countries citing papers authored by Nick Pawlowski
This map shows the geographic impact of Nick Pawlowski'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 Pawlowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nick Pawlowski more than expected).
Fields of papers citing papers by Nick Pawlowski
This network shows the impact of papers produced by Nick Pawlowski. 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 Pawlowski. The network helps show where Nick Pawlowski may publish in the future.
Co-authorship network of co-authors of Nick Pawlowski
This figure shows the co-authorship network connecting the top 25 collaborators of Nick Pawlowski. A scholar is included among the top collaborators of Nick Pawlowski 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 Nick Pawlowski. Nick Pawlowski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 5 | |
| 3 | Deep Structural Causal Models for Tractable Counterfactual Inference | 3 |
| 4 | GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery | 5 |
| 5 | 65 | |
| 6 | 75 | |
| 7 | Template Transformer Networks for Image Segmentation | 3 |
| 8 | Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders | 31 |
| 9 | 73 | |
| 10 | 4 | |
| 11 | 29 |
About Nick Pawlowski
Nick Pawlowski is a scholar working on Neurology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 11 papers that have together received 299 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (2 papers), AI in cancer detection (2 papers) and Brain Tumor Detection and Classification (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (127 citations), Computer Vision and Pattern Recognition (93 citations) and Artificial Intelligence (122 citations). Nick Pawlowski has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Ben Glocker, Nat Dilokthanakul, Kersten Petersen, Michiel Schaap, Murray Shanahan, Martin Rajchl, Daniel Rueckert, Ioannis Lavdas, Eric O. Aboagye and Andrea Rockall. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and IEEE Transactions on Neural Networks and Learning 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.