Ivan Jambor

2.9k total citations
71 papers, 1.9k citations indexed

About

Ivan Jambor is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Rheumatology. According to data from OpenAlex, Ivan Jambor has authored 71 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Pulmonary and Respiratory Medicine, 34 papers in Radiology, Nuclear Medicine and Imaging and 19 papers in Rheumatology. Recurrent topics in Ivan Jambor's work include Prostate Cancer Diagnosis and Treatment (50 papers), Prostate Cancer Treatment and Research (34 papers) and Radiomics and Machine Learning in Medical Imaging (20 papers). Ivan Jambor is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (50 papers), Prostate Cancer Treatment and Research (34 papers) and Radiomics and Machine Learning in Medical Imaging (20 papers). Ivan Jambor collaborates with scholars based in Finland, United States and Italy. Ivan Jambor's co-authors include Harri Merisaari, Pekka Taimen, Hannu J. Aronen, Peter J. Boström, Heikki Minn, M. Pesola, Jukka Kemppainen, Otto Ettala, Esa Kähkönen and Anant Madabhushi and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Ivan Jambor

68 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ivan Jambor Finland	23	1.3k	1.3k	306	229	134	71	1.9k
Tatsuo Gondo Japan	18	752 0.6×	1.0k 0.8×	473 1.5×	208 0.9×	137 1.0×	46	1.8k
Andreas M. Hötker Switzerland	20	711 0.6×	948 0.7×	246 0.8×	242 1.1×	89 0.7×	73	1.5k
Claudia Kesch Germany	24	1.1k 0.8×	2.0k 1.6×	334 1.1×	619 2.7×	125 0.9×	81	2.5k
Robert Seifert Germany	24	1.2k 0.9×	1.1k 0.8×	391 1.3×	60 0.3×	124 0.9×	122	1.9k
Ilhan Lim South Korea	21	631 0.5×	497 0.4×	190 0.6×	148 0.6×	67 0.5×	86	1.1k
Jan Philipp Radtke Germany	27	1.5k 1.2×	2.7k 2.1×	271 0.9×	825 3.6×	145 1.1×	100	3.1k
Florence Mège‐Lechevallier France	21	780 0.6×	1.5k 1.2×	118 0.4×	462 2.0×	194 1.4×	42	2.0k
Christine Schmid‐Tannwald Germany	20	922 0.7×	585 0.5×	140 0.5×	102 0.4×	56 0.4×	52	1.4k
Rodney J. Ellis United States	25	582 0.5×	1.1k 0.8×	189 0.6×	75 0.3×	192 1.4×	106	1.8k
Andrew J. Buckler United States	21	1.1k 0.8×	506 0.4×	120 0.4×	58 0.3×	264 2.0×	54	1.5k

Countries citing papers authored by Ivan Jambor

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Jambor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Jambor

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Jambor. A scholar is included among the top collaborators of Ivan Jambor 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 Ivan Jambor. Ivan Jambor 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

Malaspina, Simona, Marko Seppänen, Ivan Jambor, et al.. (2025). Prospective comparison of 18F-PSMA-1007 PET/CT and MRI with histopathology as the reference standard for intraprostatic tumour detection and T-staging of high-risk prostate cancer. European Journal of Nuclear Medicine and Molecular Imaging. 52(10). 3709–3719. 2 indexed citations

Jambor, Ivan, M. Pesola, Maria Gardberg, et al.. (2024). Relaxation Along a Fictitious Field, continuous wave T1rho, adiabatic T1rho and adiabatic T2rho imaging of human gliomas at 3T: A feasibility study. PLoS ONE. 19(4). e0296958–e0296958. 2 indexed citations

Kallonen, Teemu, Marianne Gunell, Otto Ettala, et al.. (2024). Differences in Gut Microbiota Profiles and Microbiota Steroid Hormone Biosynthesis in Men with and Without Prostate Cancer. European Urology Open Science. 62. 140–150. 7 indexed citations

Treacy, Patrick‐Julien, Ugo Giovanni Falagario, Parita Ratnani, et al.. (2023). Decipher Score predicts prostate specific antigen persistence after prostatectomy. Minerva Urology and Nephrology. 75(5). 583–590. 2 indexed citations

Beheshti, Mohsen, Pekka Taimen, Jukka Kemppainen, et al.. (2022). Value of 68Ga-labeled bombesin antagonist (RM2) in the detection of primary prostate cancer comparing with [18F]fluoromethylcholine PET-CT and multiparametric MRI—a phase I/II study. European Radiology. 33(1). 472–482. 19 indexed citations

Martini, Alberto, Ugo Giovanni Falagario, Shivaram Cumarasamy, et al.. (2021). The Role of 3D Models Obtained from Multiparametric Prostate MRI in Performing Robotic Prostatectomy. Journal of Endourology. 36(3). 387–393. 7 indexed citations

Chakravarty, Dimple, Parita Ratnani, Nihal Mohamed, et al.. (2021). Impact of diverticular disease on prostate cancer risk among hypertensive men. Prostate Cancer and Prostatic Diseases. 25(4). 700–706. 3 indexed citations

Merisaari, Harri, Heidi Liljenbäck, Helena E. Virtanen, et al.. (2021). Statistical Evaluation of Different Mathematical Models for Diffusion Weighted Imaging of Prostate Cancer Xenografts in Mice. Frontiers in Oncology. 11. 583921–583921. 2 indexed citations

Falagario, Ugo Giovanni, Ivan Jambor, Parita Ratnani, et al.. (2020). Performance of prostate multiparametric MRI for prediction of prostate cancer extra-prostatic extension according to NCCN risk categories: Implication for surgical planning. European Urology Open Science. 19. e1743–e1744. 3 indexed citations

10.

Knaapila, Juha, Ivan Jambor, Otto Ettala, et al.. (2020). Negative Predictive Value of Biparametric Prostate Magnetic Resonance Imaging in Excluding Significant Prostate Cancer: A Pooled Data Analysis Based on Clinical Data from Four Prospective, Registered Studies. European Urology Focus. 7(3). 522–531. 13 indexed citations

11.

Lantz, Anna, Ugo Giovanni Falagario, Parita Ratnani, et al.. (2020). Expanding Active Surveillance Inclusion Criteria: A Novel Nomogram Including Preoperative Clinical Parameters and Magnetic Resonance Imaging Findings. European Urology Oncology. 5(2). 187–194. 20 indexed citations

12.

Shiradkar, Rakesh, Harri Merisaari, Prateek Prasanna, et al.. (2020). Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. European Radiology. 31(1). 379–391. 22 indexed citations

13.

Perez, Ileana Montoya, Parisa Movahedi, Harri Merisaari, et al.. (2019). Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization. PLoS ONE. 14(7). e0217702–e0217702. 79 indexed citations

14.

Jambor, Ivan, Anna Kuisma, Jukka Kemppainen, et al.. (2019). Correlation between 18F-1-amino-3-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) uptake and expression of alanine-serine-cysteine-transporter 2 (ASCT2) and L-type amino acid transporter 1 (LAT1) in primary prostate cancer. EJNMMI Research. 9(1). 50–50. 16 indexed citations

15.

Falagario, Ugo Giovanni, Alberto Martini, Ethan Wajswol, et al.. (2019). Avoiding Unnecessary Magnetic Resonance Imaging (MRI) and Biopsies: Negative and Positive Predictive Value of MRI According to Prostate-specific Antigen Density, 4Kscore and Risk Calculators. European Urology Oncology. 3(5). 700–704. 72 indexed citations

16.

Knaapila, Juha, Ivan Jambor, Ileana Montoya Perez, et al.. (2019). Prebiopsy IMPROD Biparametric Magnetic Resonance Imaging Combined with Prostate-Specific Antigen Density in the Diagnosis of Prostate Cancer: An External Validation Study. European Urology Oncology. 3(5). 648–656. 21 indexed citations

17.

Jambor, Ivan, Anna Kuisma, Jukka Kemppainen, et al.. (2019). Comparison of standardized uptake values between 99mTc-HDP SPECT/CT and 18F-NaF PET/CT in bone metastases of breast and prostate cancer. EJNMMI Research. 9(1). 6–6. 48 indexed citations

18.

Movahedi, Parisa, et al.. (2016). Diffusion weighted imaging of prostate cancer: Prediction of cancer using texture features from parametric maps of the monoexponential and kurtosis functions. IEEE Conference Proceedings. 2016. 6. 1 indexed citations

19.

Merisaari, Harri, M. Pesola, Pekka Taimen, et al.. (2015). Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization. Magnetic Resonance Imaging. 33(10). 1212–1218. 22 indexed citations

20.

Jambor, Ivan, Ronald Borra, Jukka Kemppainen, et al.. (2010). Functional Imaging of Localized Prostate Cancer Aggressiveness Using ¹¹C-Acetate PET/CT and ¹H-MR Spectroscopy. Journal of Nuclear Medicine. 51(11). 1676–1683. 43 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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