Dmitry Cherezov

738 total citations
13 papers, 547 citations indexed

About

Dmitry Cherezov is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Dmitry Cherezov has authored 13 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Pulmonary and Respiratory Medicine and 6 papers in Artificial Intelligence. Recurrent topics in Dmitry Cherezov's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Lung Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (6 papers). Dmitry Cherezov is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Lung Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (6 papers). Dmitry Cherezov collaborates with scholars based in United States, China and Tanzania. Dmitry Cherezov's co-authors include Robert J. Gillies, Matthew B. Schabath, Lawrence Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Samuel Hawkins, Qian Li, Robert A. Gatenby, Olya Stringfield and Ying Liu and has published in prestigious journals such as Scientific Reports, IEEE Access and Medical Physics.

In The Last Decade

Dmitry Cherezov

12 papers receiving 540 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dmitry Cherezov United States 8 515 361 170 100 60 13 547
Mostafa Nazari Iran 11 498 1.0× 227 0.6× 188 1.1× 103 1.0× 52 0.9× 18 562
Elisabeth Pfaehler Netherlands 15 649 1.3× 252 0.7× 186 1.1× 67 0.7× 105 1.8× 31 721
M.V. Villas Spain 5 436 0.8× 179 0.5× 197 1.2× 68 0.7× 82 1.4× 6 503
Chuanmiao Xie China 5 521 1.0× 173 0.5× 294 1.7× 73 0.7× 112 1.9× 11 584
Ronrick Da‐ano France 7 460 0.9× 194 0.5× 163 1.0× 76 0.8× 73 1.2× 9 490
J. van der Stoep Netherlands 7 451 0.9× 308 0.9× 122 0.7× 61 0.6× 28 0.5× 13 613
Bao Feng China 10 345 0.7× 202 0.6× 85 0.5× 80 0.8× 40 0.7× 32 413
Tobias Fechter Germany 13 453 0.9× 426 1.2× 80 0.5× 35 0.3× 41 0.7× 32 628
Kanabu Nawa Japan 9 385 0.7× 170 0.5× 137 0.8× 58 0.6× 31 0.5× 23 495
Martijn P. A. Starmans Netherlands 12 287 0.6× 168 0.5× 63 0.4× 59 0.6× 50 0.8× 29 401

Countries citing papers authored by Dmitry Cherezov

Since Specialization
Citations

This map shows the geographic impact of Dmitry Cherezov'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 Cherezov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Cherezov more than expected).

Fields of papers citing papers by Dmitry Cherezov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dmitry Cherezov. 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 Cherezov. The network helps show where Dmitry Cherezov may publish in the future.

Co-authorship network of co-authors of Dmitry Cherezov

This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Cherezov. A scholar is included among the top collaborators of Dmitry Cherezov 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 Cherezov. Dmitry Cherezov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Cherezov, Dmitry, Harriet Kisembo, Bruce Kirenga, et al.. (2025). Opportunistic use of artificial intelligence with X-ray imaging for diagnosis of HIV status in tuberculosis patients in Uganda and Tanzania. PLOS Digital Health. 4(9). e0000988–e0000988.
2.
Cherezov, Dmitry, Vidya Sankar Viswanathan, Pingfu Fu, Amit Gupta, & Anant Madabhushi. (2023). Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study. Computer Methods and Programs in Biomedicine. 244. 107990–107990. 2 indexed citations
3.
Zurek, Eduardo, et al.. (2021). A Radiogenomics Ensemble to Predict EGFR and KRAS Mutations in NSCLC. Tomography. 7(2). 154–168. 21 indexed citations
4.
Paul, Rahul, Dmitry Cherezov, Matthew B. Schabath, et al.. (2021). Deep radiomics: deep learning on radiomics texture images. 66–66. 4 indexed citations
5.
Cherezov, Dmitry, Rahul Paul, Robert J. Gillies, et al.. (2020). Lung Nodule Sizes Are Encoded When Scaling CT Image for CNN's. Tomography. 6(2). 209–215. 7 indexed citations
6.
Cherezov, Dmitry, Dmitry B. Goldgof, Lawrence Hall, et al.. (2019). Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness. Scientific Reports. 9(1). 4500–4500. 34 indexed citations
7.
Tunali, Ilke, Lawrence Hall, Sandy Napel, et al.. (2019). Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions. Medical Physics. 46(11). 5075–5085. 53 indexed citations
8.
Paul, Rahul, Dmitry Cherezov, Matthew B. Schabath, et al.. (2019). Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. 67. 143–143. 3 indexed citations
9.
Cherezov, Dmitry, et al.. (2018). Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access. 6. 77796–77806. 74 indexed citations
10.
Cherezov, Dmitry, Samuel Hawkins, Dmitry B. Goldgof, et al.. (2018). Delta radiomic features improve prediction for lung cancer incidence: A nested case–control analysis of the National Lung Screening Trial. Cancer Medicine. 7(12). 6340–6356. 28 indexed citations
11.
Kalpathy–Cramer, Jayashree, Binsheng Zhao, Lin Lü, et al.. (2016). Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features. Tomography. 2(4). 430–437. 96 indexed citations
12.
Cherezov, Dmitry, Samuel Hawkins, Dmitry Goldgof, et al.. (2016). Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. PubMed. 2016. 1939–1944. 5 indexed citations
13.
Hawkins, Samuel, Hua Wang, Ying Liu, et al.. (2016). Predicting Malignant Nodules from Screening CT Scans. Journal of Thoracic Oncology. 11(12). 2120–2128. 220 indexed citations

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.

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