Dmitry Goldgof
- Radiology, Nuclear Medicine and Imaging top 2%
- Biomedical Engineering
- Pulmonary and Respiratory Medicine top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Matthew B. SchabathRobert J. GilliesYoganand BalagurunathanDylan HuntLaurence E. CourtGhanim UllahMahmoud A. AbdalahGeoffrey Zhang
- Topics
- Radiomics and Machine Learning in Medical Imaging (7 papers)AI in cancer detection (6 papers)Cell Image Analysis Techniques (6 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsComputer Vision and Pattern Recognition
- Partner nations
- United StatesCzechiaSaudi Arabia
In The Last Decade
Dmitry Goldgof
24 papers receiving 822 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Radiology, Nuclear Medicine and Imaging 602
- Biomedical Engineering 249
- Pulmonary and Respiratory Medicine 231
- Artificial Intelligence 169
- Computer Vision and Pattern Recognition 157
Countries citing papers authored by Dmitry Goldgof
This map shows the geographic impact of Dmitry Goldgof'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 Dmitry Goldgof with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Goldgof more than expected).
Fields of papers citing papers by Dmitry Goldgof
This network shows the impact of papers produced by Dmitry Goldgof. 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 Dmitry Goldgof. The network helps show where Dmitry Goldgof may publish in the future.
Co-authorship network of co-authors of Dmitry Goldgof
This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Goldgof. A scholar is included among the top collaborators of Dmitry Goldgof 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 Dmitry Goldgof. Dmitry Goldgof is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 23 | |
| 8 | 1 | |
| 9 | 13 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 5 | |
| 14 | 133 | |
| 15 | 6 | |
| 16 | 52 | |
| 17 | 12 | |
| 18 | PERFORMANCE EVALUATION PROTOCOL FOR FACE, PERSON AND VEHICLE DETECTION & TRACKING IN VIDEO ANALYSIS AND CONTENT EXTRACTION (VACE-II) CLEAR - CLASSIFICATION OF EVENTS, ACTIVITIES AND RELATIONSHIPS | 14 |
| 19 | 71 | |
| 20 | 15 |
About Dmitry Goldgof
Dmitry Goldgof is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Neurology, having authored 27 papers that have together received 841 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (6 papers) and Cell Image Analysis Techniques (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (602 citations), Health Informatics (25 citations) and Computer Vision and Pattern Recognition (157 citations). Dmitry Goldgof has collaborated with scholars based in United States, Czechia and Saudi Arabia. Frequent co-authors include Matthew B. Schabath, Robert J. Gillies, Yoganand Balagurunathan, Dylan Hunt, Laurence E. Court, Ghanim Ullah, Mahmoud A. Abdalah, Geoffrey Zhang, Kujtim Latifi and Dennis Mackin. Their work appears in journals such as Pattern Recognition, Medical Physics and IEEE Transactions on Aerospace and Electronic 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.