Pasquale Tamborra

938 total citations
29 papers, 682 citations indexed

About

Pasquale Tamborra is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Pasquale Tamborra has authored 29 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Artificial Intelligence and 8 papers in Cancer Research. Recurrent topics in Pasquale Tamborra's work include Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (14 papers) and Breast Cancer Treatment Studies (8 papers). Pasquale Tamborra is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (14 papers) and Breast Cancer Treatment Studies (8 papers). Pasquale Tamborra collaborates with scholars based in Italy. Pasquale Tamborra's co-authors include Raffaella Massafra, Annarita Fanizzi, Vittorio Didonna, Daniele La Forgia, R. Bellotti, Sabina Tangaro, Vito Lorusso, Alfredo Zito, Agnese Latorre and Samantha Bove and has published in prestigious journals such as PLoS ONE, Scientific Reports and BMC Bioinformatics.

In The Last Decade

Pasquale Tamborra

28 papers receiving 674 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pasquale Tamborra Italy 16 486 392 124 120 102 29 682
Vittorio Didonna Italy 17 520 1.1× 419 1.1× 124 1.0× 138 1.1× 108 1.1× 33 726
Lan Li China 15 632 1.3× 228 0.6× 93 0.8× 140 1.2× 124 1.2× 51 908
Lakshmanan Sannachi Canada 18 689 1.4× 322 0.8× 137 1.1× 68 0.6× 266 2.6× 57 834
Alexandra Edwards United States 15 533 1.1× 484 1.2× 54 0.4× 226 1.9× 70 0.7× 33 797
Zixiao Lu China 10 380 0.8× 265 0.7× 107 0.9× 56 0.5× 65 0.6× 20 602
Neha Bhooshan United States 12 355 0.7× 222 0.6× 86 0.7× 227 1.9× 33 0.3× 28 773
F. W. Samuelson United States 11 292 0.6× 209 0.5× 72 0.6× 183 1.5× 117 1.1× 53 657
Belinda Curpen Canada 17 478 1.0× 274 0.7× 227 1.8× 85 0.7× 100 1.0× 49 837
Hadi Tadayyon Canada 15 516 1.1× 224 0.6× 78 0.6× 44 0.4× 273 2.7× 33 670
Zeyan Xu China 13 440 0.9× 301 0.8× 70 0.6× 91 0.8× 69 0.7× 42 758

Countries citing papers authored by Pasquale Tamborra

Since Specialization
Citations

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

Fields of papers citing papers by Pasquale Tamborra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pasquale Tamborra

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

All Works

20 of 20 papers shown
1.
Comes, Maria Colomba, Annarita Fanizzi, Samantha Bove, et al.. (2024). Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy. Computers in Biology and Medicine. 172. 108132–108132. 8 indexed citations
2.
Fanizzi, Annarita, Domenico Pomarico, Alessandro Rizzo, et al.. (2023). Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer. Scientific Reports. 13(1). 8575–8575. 5 indexed citations
3.
Massafra, Raffaella, Samantha Bove, Daniele La Forgia, et al.. (2022). An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients’ Age: A Retrospective Cohort Study. Cancers. 14(9). 2215–2215. 6 indexed citations
4.
Fanizzi, Annarita, Samantha Bove, Maria Colomba Comes, et al.. (2022). Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer. Frontiers in Medicine. 9. 993395–993395. 5 indexed citations
5.
Massafra, Raffaella, Maria Colomba Comes, Samantha Bove, et al.. (2022). A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification. PLoS ONE. 17(9). e0274691–e0274691. 11 indexed citations
6.
Bove, Samantha, Maria Colomba Comes, Vito Lorusso, et al.. (2022). A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients. Scientific Reports. 12(1). 7914–7914. 30 indexed citations
7.
Placidi, Lorenzo, Cristina Garibaldi, T. Rancati, et al.. (2021). A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity. Cancers. 13(15). 3835–3835. 36 indexed citations
8.
Comes, Maria Colomba, Annarita Fanizzi, Samantha Bove, et al.. (2021). Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs. Scientific Reports. 11(1). 14123–14123. 54 indexed citations
9.
Comes, Maria Colomba, Daniele La Forgia, Vittorio Didonna, et al.. (2021). Early Prediction of Breast Cancer Recurrence for Patients Treated with Neoadjuvant Chemotherapy: A Transfer Learning Approach on DCE-MRIs. Cancers. 13(10). 2298–2298. 34 indexed citations
10.
Massafra, Raffaella, Agnese Latorre, Annarita Fanizzi, et al.. (2021). A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results. Frontiers in Oncology. 11. 576007–576007. 28 indexed citations
11.
Fanizzi, Annarita, Teresa M. A. Basile, L. Losurdo, et al.. (2020). A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis. BMC Bioinformatics. 21(S2). 91–91. 42 indexed citations
12.
Forgia, Daniele La, Annarita Fanizzi, Francesco Campobasso, et al.. (2020). Radiomic Analysis in Contrast-Enhanced Spectral Mammography for Predicting Breast Cancer Histological Outcome. Diagnostics. 10(9). 708–708. 76 indexed citations
13.
Basile, Teresa M. A., Annarita Fanizzi, L. Losurdo, et al.. (2019). Microcalcification detection in full-field digital mammograms: A fully automated computer-aided system. Physica Medica. 64. 1–9. 43 indexed citations
14.
Losurdo, L., Annarita Fanizzi, Teresa M. A. Basile, et al.. (2019). Radiomics Analysis on Contrast-Enhanced Spectral Mammography Images for Breast Cancer Diagnosis: A Pilot Study. Entropy. 21(11). 1110–1110. 40 indexed citations
15.
Tamborra, Pasquale, et al.. (2018). The 3D isodose structure‐based method for clinical dose distributions comparison in pretreatment patient‐QA. Medical Physics. 46(2). 426–436. 8 indexed citations
16.
Losurdo, L., Teresa M. A. Basile, Annarita Fanizzi, et al.. (2018). A Gradient-Based Approach for Breast DCE-MRI Analysis. BioMed Research International. 2018. 1–10. 24 indexed citations
17.
Basile, Teresa M. A., Annarita Fanizzi, L. Losurdo, et al.. (2017). Hough transform for clustered microcalcifications detection in full-field digital mammograms. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 41–41. 25 indexed citations
18.
19.
Fanizzi, Annarita, Sabina Tangaro, R. Bellotti, et al.. (2016). Automatised detection of microcalcification in mammography. Physica Medica. 32. 217–217. 2 indexed citations
20.
Tamborra, Pasquale, et al.. (2009). SORS: A New Software for the Simulation of Radiotherapy Schedule. Medical dosimetry. 35(3). 208–213.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Vittorio Didonna Breakdown of academic impact, for papers by Lan Li Breakdown of academic impact, for papers by Lakshmanan Sannachi Breakdown of academic impact, for papers by Alexandra Edwards Breakdown of academic impact, for papers by Zixiao Lu Breakdown of academic impact, for papers by Neha Bhooshan Breakdown of academic impact, for papers by F. W. Samuelson Breakdown of academic impact, for papers by Belinda Curpen Breakdown of academic impact, for papers by Hadi Tadayyon Breakdown of academic impact, for papers by Zeyan Xu
Rankless by CCL
2026