Joanne Hoffman
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
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- Lung Cancer Diagnosis and Treatment 5
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- Radiomics and Machine Learning in Medical Imaging 3
- COVID-19 diagnosis using AI 2
- Medical Imaging Techniques and Applications 1
- Co-authors
- Ronald M. Summers (6 shared papers)Evrim Türkbey (6 shared papers)Le Lü (4 shared papers)Shijun Wang (3 shared papers)Ari Seff (2 shared papers)Holger R. Roth (2 shared papers)Kevin M. Cherry (2 shared papers)Jiamin Liu (1 shared paper)
- Journals
- Journal of Clinical Pathology (1 paper)Medical Physics (1 paper)Lecture notes in computer science (1 paper)Zenodo (CERN European Organization for Nuclear Research) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Joanne Hoffman
7 papers receiving 479 citations
Joanne Hoffman's Hit Papers
Peers
Comparison fields: 5 of 56
- Radiology, Nuclear Medicine and Imaging 248
- Health Informatics 9
- Computer Vision and Pattern Recognition 116
- Pulmonary and Respiratory Medicine 139
- Artificial Intelligence 148
Countries citing papers authored by Joanne Hoffman
This map shows the geographic impact of Joanne Hoffman'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 Joanne Hoffman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joanne Hoffman more than expected).
Fields of papers citing papers by Joanne Hoffman
This network shows the impact of papers produced by Joanne Hoffman. 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 Joanne Hoffman. The network helps show where Joanne Hoffman may publish in the future.
Co-authors
The 16 scholars most cited alongside Joanne Hoffman, 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 | A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations Hit paper breakdown → | 2014 | 340 |
| 2 | 2014 | 46 | |
| 3 | 2016 | 41 | |
| 4 | 2010 | 36 | |
| 5 | 2014 | 20 | |
| 6 | 2014 | 4 | |
| 7 | 2015 | 3 |
About Joanne Hoffman
Joanne Hoffman is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases, having authored 7 papers that have together received 490 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (3 papers), COVID-19 diagnosis using AI (2 papers), AI in cancer detection (2 papers), Advanced Neural Network Applications (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (248 citations), Health Informatics (9 citations), Computer Vision and Pattern Recognition (116 citations), Pulmonary and Respiratory Medicine (139 citations) and Artificial Intelligence (148 citations). Joanne Hoffman has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Ronald M. Summers, Evrim Türkbey, Le Lü, Shijun Wang, Ari Seff, Holger R. Roth, Kevin M. Cherry, Jiamin Liu, Jiamin Liu and Jianhua Yao. Their work appears in journals such as Journal of Clinical Pathology, Medical Physics, Lecture notes in computer science, Zenodo (CERN European Organization for Nuclear Research) and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.