Nathan Ing
Impact in
- Health Informatics top 10%
-
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- AI in cancer detection 9
-
- Radiomics and Machine Learning in Medical Imaging 9
- Co-authors
- Arkadiusz Gertych (9 shared papers)Beatrice S. Knudsen (9 shared papers)Zhaoxuan Ma (7 shared papers)Szczepan Cierniak (2 shared papers)Tomasz Markiewicz (2 shared papers)Żaneta Świderska-Chadaj (3 shared papers)Ann E. Walts (3 shared papers)Samuel Guzman (1 shared paper)
- Journals
- Scientific Reports (2 papers)Nature Communications (1 paper)Computerized Medical Imaging and Graphics (1 paper)iScience (1 paper)Cancer Research (1 paper)
- Partner nations
- United StatesPolandCanada
In The Last Decade
Nathan Ing
13 papers receiving 451 citations
Peers
Comparison fields: 5 of 64
- Health Informatics 11
- Radiology, Nuclear Medicine and Imaging 154
- Artificial Intelligence 222
- Biophysics 35
- Computer Vision and Pattern Recognition 75
Countries citing papers authored by Nathan Ing
This map shows the geographic impact of Nathan Ing'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 Nathan Ing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Ing more than expected).
Fields of papers citing papers by Nathan Ing
This network shows the impact of papers produced by Nathan Ing. 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 Nathan Ing. The network helps show where Nathan Ing may publish in the future.
Co-authors
The 25 scholars most cited alongside Nathan Ing, 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 | 133 | |
| 2 | 2021 | 112 | |
| 3 | 2015 | 92 | |
| 4 | 2018 | 55 | |
| 5 | 2017 | 31 | |
| 6 | 2023 | 16 | |
| 7 | 2018 | 5 | |
| 8 | 2018 | 5 | |
| 9 | 2016 | 4 | |
| 10 | 2019 | 4 | |
| 11 | 2025 | 3 | |
| 12 | A deep multiple instance model to predict prostate cancer metastasis from nuclear morphology | 2018 | 2 |
| 13 | 2024 | 1 | |
| 14 | 2021 | 0 |
About Nathan Ing
Nathan Ing is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Oncology and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 463 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (9 papers), Single-cell and spatial transcriptomics (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Prostate Cancer Diagnosis and Treatment (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Renal cell carcinoma treatment (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (154 citations), Artificial Intelligence (222 citations), Biophysics (35 citations) and Computer Vision and Pattern Recognition (75 citations). Nathan Ing has collaborated with scholars based in United States, Poland and Canada. Frequent co-authors include Arkadiusz Gertych, Beatrice S. Knudsen, Zhaoxuan Ma, Szczepan Cierniak, Tomasz Markiewicz, Żaneta Świderska-Chadaj, Ann E. Walts, Samuel Guzman, Mahul B. Amin and Simon Knott. Their work appears in journals such as Scientific Reports, Nature Communications, Computerized Medical Imaging and Graphics, iScience and Cancer Research.
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.