Jeremy Wohlwend
- Radiology, Nuclear Medicine and Imaging
- Pulmonary and Respiratory Medicine
- Artificial Intelligence
- Molecular Biology
- Biomedical Engineering
- Co-authors
- Regina BarzilayLecia V. SequistPeter G. MikhaelFlorian J. FintelmannRamnik J. XavierMartin StražarConnor W. ColeySamuel Goldman
- Topics
- Topic Modeling (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Lung Cancer Diagnosis and Treatment (2 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Partner nations
- United StatesSouth KoreaTaiwan
In The Last Decade
Jeremy Wohlwend
11 papers receiving 212 citations
Hit Papers
Peers
Comparison fields: 5 of 66
- Radiology, Nuclear Medicine and Imaging 90
- Pulmonary and Respiratory Medicine 73
- Artificial Intelligence 70
- Molecular Biology 42
- Biomedical Engineering 25
Countries citing papers authored by Jeremy Wohlwend
This map shows the geographic impact of Jeremy Wohlwend'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 Jeremy Wohlwend with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy Wohlwend more than expected).
Fields of papers citing papers by Jeremy Wohlwend
This network shows the impact of papers produced by Jeremy Wohlwend. 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 Jeremy Wohlwend. The network helps show where Jeremy Wohlwend may publish in the future.
Co-authorship network of co-authors of Jeremy Wohlwend
This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy Wohlwend. A scholar is included among the top collaborators of Jeremy Wohlwend 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 Jeremy Wohlwend. Jeremy Wohlwend 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 | 1 | |
| 3 | 39 | |
| 4 | Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomographybreakdown → | 114 |
| 5 | 16 | |
| 6 | 13 | |
| 7 | 11 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 12 | |
| 11 | Body-form and body-pose recognition with a hierarchical model of the ventral stream | 1 |
About Jeremy Wohlwend
Jeremy Wohlwend is a scholar working on Biophysics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 11 papers that have together received 221 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (24 citations), Radiology, Nuclear Medicine and Imaging (90 citations) and Pulmonary and Respiratory Medicine (73 citations). Jeremy Wohlwend has collaborated with scholars based in United States, South Korea and Taiwan. Frequent co-authors include Regina Barzilay, Lecia V. Sequist, Peter G. Mikhael, Florian J. Fintelmann, Ramnik J. Xavier, Martin Stražar, Connor W. Coley, Samuel Goldman, A. Takigami and PuiYee Chan. Their work appears in journals such as Nature Medicine, Journal of Clinical Oncology and Nature Machine Intelligence.
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.