P. De Marco

771 total citations
26 papers, 512 citations indexed

About

P. De Marco is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, P. De Marco has authored 26 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Biomedical Engineering and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in P. De Marco's work include Advanced X-ray and CT Imaging (13 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Medical Imaging Techniques and Applications (10 papers). P. De Marco is often cited by papers focused on Advanced X-ray and CT Imaging (13 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Medical Imaging Techniques and Applications (10 papers). P. De Marco collaborates with scholars based in Italy, United Kingdom and Myanmar. P. De Marco's co-authors include Daniela Origgi, Massimo Bellomi, Lorenzo Spaggiari, Giulia Veronesi, Patrick Maisonneuve, Cristiano Rampinelli, Monica Casiraghi, P.E. Colombo, Mahila Ferrari and Stefania Rizzo and has published in prestigious journals such as International Journal of Molecular Sciences, BMJ and European Radiology.

In The Last Decade

P. De Marco

23 papers receiving 505 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
P. De Marco Italy 11 364 260 178 67 51 26 512
Artit Jirapatnakul United States 15 443 1.2× 383 1.5× 110 0.6× 66 1.0× 50 1.0× 42 611
C Furstoss Canada 4 351 1.0× 116 0.4× 124 0.7× 71 1.1× 56 1.1× 9 408
Yao Ai China 13 306 0.8× 119 0.5× 52 0.3× 46 0.7× 44 0.9× 28 378
Ahmad Algohary United States 8 367 1.0× 274 1.1× 84 0.5× 75 1.1× 40 0.8× 16 440
Shane P. Krafft United States 11 253 0.7× 216 0.8× 83 0.5× 28 0.4× 57 1.1× 24 380
Junfeng Xiong China 10 311 0.9× 251 1.0× 50 0.3× 61 0.9× 59 1.2× 22 366
Mingyu Tan China 7 238 0.7× 175 0.7× 95 0.5× 37 0.6× 14 0.3× 18 334
L. Van den Bosch Netherlands 10 197 0.5× 182 0.7× 64 0.4× 38 0.6× 54 1.1× 24 520
Bradley G. Ackerson United States 8 115 0.3× 188 0.7× 38 0.2× 29 0.4× 90 1.8× 18 309
Zongrui Ma China 8 192 0.5× 79 0.3× 58 0.3× 34 0.5× 25 0.5× 13 236

Countries citing papers authored by P. De Marco

Since Specialization
Citations

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

Fields of papers citing papers by P. De Marco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. De Marco. 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 P. De Marco. The network helps show where P. De Marco may publish in the future.

Co-authorship network of co-authors of P. De Marco

This figure shows the co-authorship network connecting the top 25 collaborators of P. De Marco. A scholar is included among the top collaborators of P. De Marco 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 P. De Marco. P. De Marco 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.
Nicosia, Luca, Aurora Gaeta, Sara Raimondi, et al.. (2025). Preliminary Evaluation of Radiomics in Contrast-Enhanced Mammography for Prognostic Prediction of Breast Cancer. Cancers. 17(12). 1926–1926.
2.
Bruschi, Giulia, et al.. (2025). Phantom‐based comparative analysis of contrast‐enhanced mammography systems: Image quality and performance evaluation. Journal of Applied Clinical Medical Physics. 26(7). e70163–e70163.
3.
Marco, P. De, et al.. (2025). Effective Dose Estimation in Computed Tomography by Machine Learning. Tomography. 11(1). 2–2.
4.
Pesapane, Filippo, Anna Rotili, Elisa Scalco, et al.. (2025). Predictive value of tumoral and peritumoral radiomic features in neoadjuvant chemotherapy response for breast cancer: a retrospective study. La radiologia medica. 130(5). 598–612. 2 indexed citations
5.
Marco, P. De, et al.. (2024). Transfer learning classification of suspicious lesions on breast ultrasound: is there room to avoid biopsies of benign lesions?. European Radiology Experimental. 8(1). 121–121. 1 indexed citations
6.
Maran, Daniela Acquadro, et al.. (2024). Remote workers’ life quality and stress during COVID-19: a systematic review. European Journal of Public Health. 35(1). 141–152. 2 indexed citations
7.
Nicosia, Luca, Anna Carla Bozzini, Filippo Pesapane, et al.. (2023). Breast Digital Tomosynthesis versus Contrast-Enhanced Mammography: Comparison of Diagnostic Application and Radiation Dose in a Screening Setting. Cancers. 15(9). 2413–2413. 15 indexed citations
8.
Pesapane, Filippo, P. De Marco, Serena Carriero, et al.. (2023). Advancements in Standardizing Radiological Reports: A Comprehensive Review. Medicina. 59(9). 1679–1679. 18 indexed citations
9.
Pesapane, Filippo, P. De Marco, Luca Nicosia, et al.. (2023). How Radiomics Can Improve Breast Cancer Diagnosis and Treatment. Journal of Clinical Medicine. 12(4). 1372–1372. 40 indexed citations
10.
Nicosia, Luca, Filippo Pesapane, Anna Carla Bozzini, et al.. (2023). Prediction of the Malignancy of a Breast Lesion Detected on Breast Ultrasound: Radiomics Applied to Clinical Practice. Cancers. 15(3). 964–964. 8 indexed citations
11.
Rinaldi, Lisa, Tommaso Santaniello, P. De Marco, et al.. (2022). HeLLePhant: A phantom mimicking non-small cell lung cancer for texture analysis in CT images. Physica Medica. 97. 13–24. 10 indexed citations
12.
Marco, P. De, D. Ciardo, S. Comi, et al.. (2020). Influence of different urinary bladder filling levels and controlling regions of interest selection on deformable image registration algorithms. Physica Medica. 75. 19–25. 1 indexed citations
13.
Marco, P. De, R. Ricotti, M.C. Leonardi, et al.. (2019). Image quality and dose evaluation of MVCT TomoTherapy acquisitions: A phantom study. Physica Medica. 57. 200–206. 13 indexed citations
14.
Volpe, Stefania, Barbara Alicja Jereczek‐Fossa, Dario Zerini, et al.. (2018). Case series on multiple prostate re-irradiation for locally recurrent prostate cancer: something ventured, something gained. Neoplasma. 66(2). 308–314. 4 indexed citations
15.
Garibaldi, Cristina, Cristiana Fodor, Giulia Riva, et al.. (2018). Cone-beam CT-based inter-fraction localization errors for tumors in the pelvic region. Physica Medica. 46. 59–66. 4 indexed citations
16.
Marco, P. De & Daniela Origgi. (2018). New adaptive statistical iterative reconstruction ASiR‐V: Assessment of noise performance in comparison to ASiR. Journal of Applied Clinical Medical Physics. 19(2). 275–286. 47 indexed citations
17.
Rampinelli, Cristiano, P. De Marco, Daniela Origgi, et al.. (2017). Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis. BMJ. 356. j347–j347. 192 indexed citations
18.
Rizzo, Stefania, Davide Radice, Marco Femia, et al.. (2017). Metastatic and non-metastatic lymph nodes: quantification and different distribution of iodine uptake assessed by dual-energy CT. European Radiology. 28(2). 760–769. 59 indexed citations
19.
Marvaso, Giulia, Barbara Alicja Jereczek‐Fossa, Giulia Riva, et al.. (2017). High-Risk Prostate Cancer and Radiotherapy: The Past and the Future. A Benchmark for a New Mixed Beam Radiotherapy Approach. Clinical Genitourinary Cancer. 15(3). 376–383. 5 indexed citations
20.
Marco, P. De, et al.. (2016). Digital breast tomosynthesis: Dose and image quality assessment. Physica Medica. 33. 56–67. 32 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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