William E. Lotter
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 11
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- Artificial Intelligence in Healthcare and Education 3
- Co-authors
- David Cox (4 shared papers)Kevin Wu (3 shared papers)Greg Sorensen (1 shared paper)Gabriel Kreiman (2 shared papers)Eric Hsiao‐Kuang Wu (2 shared papers)Abdul Rahman Diab (5 shared papers)Jiye G. Kim (4 shared papers)Giorgia Grisot (3 shared papers)
- Journals
- Radiology Artificial Intelligence (3 papers)JAMA Network Open (2 papers)Journal of the American Academy of Dermatology (2 papers)npj Digital Medicine (2 papers)BMJ Open (1 paper)
- Partner nations
- United StatesAustraliaChina
In The Last Decade
William E. Lotter
27 papers receiving 1.4k citations
William E. Lotter's Hit Papers
Peers
Comparison fields: 5 of 129
- Health Informatics 199
- Radiology, Nuclear Medicine and Imaging 513
- Artificial Intelligence 712
- Cognitive Neuroscience 138
- Health Information Management 32
Countries citing papers authored by William E. Lotter
This map shows the geographic impact of William E. Lotter'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 William E. Lotter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William E. Lotter more than expected).
Fields of papers citing papers by William E. Lotter
This network shows the impact of papers produced by William E. Lotter. 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 William E. Lotter. The network helps show where William E. Lotter may publish in the future.
Co-authors
The 25 scholars most cited alongside William E. Lotter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms Hit paper breakdown → | 2020 | 306 |
| 2 | Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach. Hit paper breakdown → | 2021 | 287 |
| 3 | 2018 | 119 | |
| 4 | 2018 | 109 | |
| 5 | Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions Hit paper breakdown → | 2024 | 108 |
| 6 | 2017 | 105 | |
| 7 | 2024 | 70 | |
| 8 | 2023 | 64 | |
| 9 | 2020 | 61 | |
| 10 | 2022 | 40 | |
| 11 | 2024 | 28 | |
| 12 | 2022 | 23 | |
| 13 | 2021 | 21 | |
| 14 | 2022 | 18 | |
| 15 | 2025 | 17 | |
| 16 | 2025 | 13 | |
| 17 | 2024 | 12 | |
| 18 | 2024 | 9 | |
| 19 | 2025 | 7 | |
| 20 | 2025 | 5 |
About William E. Lotter
William E. Lotter is a scholar working on Artificial Intelligence, Health Informatics, Oncology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 30 papers that have together received 1.4k indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Digital Radiography and Breast Imaging (4 papers), Nonmelanoma Skin Cancer Studies (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Global Cancer Incidence and Screening (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Health Informatics (199 citations), Radiology, Nuclear Medicine and Imaging (513 citations), Artificial Intelligence (712 citations), Cognitive Neuroscience (138 citations) and Health Information Management (32 citations). William E. Lotter has collaborated with scholars based in United States, Australia and China. Frequent co-authors include David Cox, Kevin Wu, Greg Sorensen, Gabriel Kreiman, Eric Hsiao‐Kuang Wu, Abdul Rahman Diab, Jiye G. Kim, Giorgia Grisot, Bryan Haslam and Gopal R. Vijayaraghavan. Their work appears in journals such as Radiology Artificial Intelligence, JAMA Network Open, Journal of the American Academy of Dermatology, npj Digital Medicine and BMJ Open.
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.