Sergey Primakov

1.8k total citations · 1 hit paper
25 papers, 1.0k citations indexed

About

Sergey Primakov is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Sergey Primakov has authored 25 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Artificial Intelligence and 8 papers in Biomedical Engineering. Recurrent topics in Sergey Primakov's work include Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Imaging Techniques and Applications (9 papers) and AI in cancer detection (9 papers). Sergey Primakov is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Imaging Techniques and Applications (9 papers) and AI in cancer detection (9 papers). Sergey Primakov collaborates with scholars based in Netherlands, Germany and Belgium. Sergey Primakov's co-authors include Philippe Lambin, Abdalla Ibrahim, Henry C. Woodruff, Turkey Refaee, Renée W. Y. Granzier, Manon Beuque, Sebastian Sanduleanu, Guangyao Wu, Felix M. Mottaghy and Simon Keek and has published in prestigious journals such as PLoS ONE, Scientific Reports and Radiology.

In The Last Decade

Sergey Primakov

25 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Radiomics: from qualitative to quantitative imaging

2020 224 citations Turkey Refaee, Renée W. Y. Granzier et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sergey Primakov Netherlands	15	828	328	247	211	126	25	1.0k
Turkey Refaee Saudi Arabia	14	872 1.1×	319 1.0×	384 1.6×	179 0.8×	133 1.1×	31	1.1k
Vishwa S. Parekh United States	14	722 0.9×	213 0.6×	154 0.6×	252 1.2×	128 1.0×	39	942
Tyler Bradshaw United States	19	1.1k 1.3×	372 1.1×	276 1.1×	119 0.6×	125 1.0×	63	1.4k
Sarah A. Mattonen Canada	13	796 1.0×	214 0.7×	457 1.9×	171 0.8×	138 1.1×	36	963
Ghasem Hajianfar Iran	20	1.0k 1.2×	391 1.2×	329 1.3×	210 1.0×	77 0.6×	86	1.2k
Shufang Pei China	12	833 1.0×	137 0.4×	212 0.9×	229 1.1×	134 1.1×	23	1.0k
Cristiana Fanciullo Italy	6	726 0.9×	244 0.7×	251 1.0×	140 0.7×	131 1.0×	10	867
Emine Şebnem Durmaz Türkiye	15	672 0.8×	182 0.6×	349 1.4×	114 0.5×	94 0.7×	26	915
Lijun Lu China	20	1.1k 1.3×	394 1.2×	358 1.4×	149 0.7×	155 1.2×	83	1.3k
Magda Marcon Switzerland	20	882 1.1×	249 0.8×	277 1.1×	524 2.5×	91 0.7×	63	1.5k

Countries citing papers authored by Sergey Primakov

Since Specialization

Citations

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

Fields of papers citing papers by Sergey Primakov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergey Primakov

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

All Works

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20 of 20 papers shown

Primakov, Sergey, et al.. (2023). Precision-medicine-toolbox: An open-source python package for the quantitative medical image analysis. Software Impacts. 16. 100508–100508. 3 indexed citations

Ibrahim, Abdalla, Akshayaa Vaidyanathan, Sergey Primakov, et al.. (2023). Deep learning based identification of bone scintigraphies containing metastatic bone disease foci. Cancer Imaging. 23(1). 12–12. 11 indexed citations

Beuque, Manon, Marc B. I. Lobbes, Yvonka van Wijk, et al.. (2023). Combining Deep Learning and Handcrafted Radiomics for Classification of Suspicious Lesions on Contrast-enhanced Mammograms. Radiology. 307(5). e221843–e221843. 42 indexed citations

Halilaj, Iva, Cary Oberije, Avishek Chatterjee, et al.. (2022). Open Source Repository and Online Calculator of Prediction Models for Diagnosis and Prognosis in Oncology. Biomedicines. 10(11). 2679–2679. 3 indexed citations

Keek, Simon, Manon Beuque, Sergey Primakov, et al.. (2022). Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics. Frontiers in Oncology. 12. 920393–920393. 8 indexed citations

Primakov, Sergey, et al.. (2022). Beyond automatic medical image segmentation—the spectrum between fully manual and fully automatic delineation. Physics in Medicine and Biology. 67(12). 12TR01–12TR01. 18 indexed citations

Refaee, Turkey, Zohaib Salahuddin, Sergey Primakov, et al.. (2022). CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features. Journal of Personalized Medicine. 12(4). 553–553. 8 indexed citations

Granzier, Renée W. Y., Abdalla Ibrahim, Sergey Primakov, et al.. (2021). MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study. Cancers. 13(10). 2447–2447. 26 indexed citations

Ibrahim, Abdalla, Henry C. Woodruff, Vincent Andrearczyk, et al.. (2021). Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods. Journal of Personalized Medicine. 11(9). 842–842. 116 indexed citations

10.

Keek, Simon, Frederik Wesseling, Henry C. Woodruff, et al.. (2021). A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images. Cancers. 13(13). 3271–3271. 19 indexed citations

11.

Ibrahim, Abdalla, Turkey Refaee, Ralph T. H. Leijenaar, et al.. (2021). The application of a workflow integrating the variable reproducibility and harmonizability of radiomic features on a phantom dataset. PLoS ONE. 16(5). e0251147–e0251147. 30 indexed citations

12.

Vaidyanathan, Akshayaa, Ralph T. H. Leijenaar, Marc van Hoof, et al.. (2021). Deep learning for the fully automated segmentation of the inner ear on MRI. Scientific Reports. 11(1). 2885–2885. 44 indexed citations

13.

Samiei, Sanaz, Renée W. Y. Granzier, Abdalla Ibrahim, et al.. (2021). Dedicated Axillary MRI-Based Radiomics Analysis for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer. Cancers. 13(4). 757–757. 25 indexed citations

14.

Primakov, Sergey, Janita E. van Timmeren, Guorong Wu, et al.. (2021). OC-0557 AI-based NSCLC detection and segmentation: faster and more prognostic than manual segmentation. Radiotherapy and Oncology. 161. S441–S443. 1 indexed citations

15.

Ibrahim, Abdalla, Turkey Refaee, Sergey Primakov, et al.. (2021). The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features’ Stability with and without ComBat Harmonization. Cancers. 13(8). 1848–1848. 40 indexed citations

16.

Ibrahim, Abdalla, Turkey Refaee, Sergey Primakov, et al.. (2021). Reproducibility of CT-Based Hepatocellular Carcinoma Radiomic Features across Different Contrast Imaging Phases: A Proof of Concept on SORAMIC Trial Data. Cancers. 13(18). 4638–4638. 14 indexed citations

17.

Ibrahim, Abdalla, Sergey Primakov, Manon Beuque, et al.. (2020). Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework. Methods. 188. 20–29. 166 indexed citations

18.

Kalmet, Pishtiwan H. S., Sebastian Sanduleanu, Sergey Primakov, et al.. (2020). Deep learning in fracture detection: a narrative review. Acta Orthopaedica. 91(2). 215–220. 109 indexed citations

19.

Kalmet, Pishtiwan H. S., Sebastian Sanduleanu, Sergey Primakov, et al.. (2020). Deep learning in fracture detection: a narrative review. Acta Orthopaedica. 91(3). 362–362. 9 indexed citations

20.

Ibrahim, Abdalla, Martin Vallières, Henry C. Woodruff, et al.. (2019). Radiomics Analysis for Clinical Decision Support in Nuclear Medicine. Seminars in Nuclear Medicine. 49(5). 438–449. 37 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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