Camilla Scapicchio

553 total citations · 1 hit paper
9 papers, 336 citations indexed

About

Camilla Scapicchio is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Camilla Scapicchio has authored 9 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Artificial Intelligence and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Camilla Scapicchio's work include Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (6 papers) and Medical Imaging Techniques and Applications (2 papers). Camilla Scapicchio is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (6 papers) and Medical Imaging Techniques and Applications (2 papers). Camilla Scapicchio collaborates with scholars based in Italy, Spain and Czechia. Camilla Scapicchio's co-authors include Emanuele Neri, Michela Gabelloni, Dania Cioni, Luca Saba, Andrea Barucci, Carlo Cavaliere, Peppino Mirabelli, Valentina Brancato, Marco Salvatore and Luigi Coppola and has published in prestigious journals such as European Radiology, Applied Sciences and Journal of Translational Medicine.

In The Last Decade

Camilla Scapicchio

6 papers receiving 330 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.

A deep look into radiomics

2021 259 citations Camilla Scapicchio, Michela Gabelloni et al. La radiologia medica profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Camilla Scapicchio Italy	5	254	85	70	68	65	9	336
João Santinha Portugal	11	210 0.8×	52 0.6×	71 1.0×	56 0.8×	69 1.1×	30	326
Khashayar Namdar Canada	10	280 1.1×	71 0.8×	109 1.6×	81 1.2×	49 0.8×	26	470
Martijn P. A. Starmans Netherlands	12	287 1.1×	63 0.7×	168 2.4×	59 0.9×	50 0.8×	29	401
Domiziana Santucci Italy	14	254 1.0×	71 0.8×	106 1.5×	90 1.3×	60 0.9×	56	458
D. Schött United States	8	302 1.2×	82 1.0×	85 1.2×	89 1.3×	164 2.5×	16	360
Gaia Ninatti Italy	8	182 0.7×	51 0.6×	72 1.0×	49 0.7×	37 0.6×	18	249
Mireia Crispin‐Ortuzar United Kingdom	10	337 1.3×	92 1.1×	109 1.6×	121 1.8×	67 1.0×	27	471
Yayuan Geng China	11	286 1.1×	66 0.8×	106 1.5×	41 0.6×	75 1.2×	21	358
Bao Feng China	10	345 1.4×	85 1.0×	202 2.9×	80 1.2×	40 0.6×	32	413

Countries citing papers authored by Camilla Scapicchio

Since Specialization

Citations

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

Fields of papers citing papers by Camilla Scapicchio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Camilla Scapicchio

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Damiani, Silvestro, et al.. (2025). Deep Learning Denoising of Low-Dose Computed Tomography Using Convolutional Autoencoder: A Phantom Study. 376–385.

2.

Berti, Andrea, Camilla Scapicchio, Chiara Iacconi, et al.. (2025). An explainable-by-design end-to-end AI framework based on prototypical part learning for lesion detection and classification in Digital Breast Tomosynthesis images. Computational and Structural Biotechnology Journal. 27. 2649–2660.

3.

Brancato, Valentina, Luigi Coppola, Carlo Cavaliere, et al.. (2024). Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine. Journal of Translational Medicine. 22(1). 136–136. 34 indexed citations

4.

Retico, Alessandra, et al.. (2024). Explainability Applied to a Deep-Learning Based Algorithm for Lung Nodule Segmentation. CINECA IRIS Institutial research information system (University of Pisa). 132–138.

5.

Gabelloni, Michela, Lorenzo Faggioni, Giuliana Restante, et al.. (2022). Bridging gaps between images and data: a systematic update on imaging biobanks. European Radiology. 32(5). 3173–3186. 22 indexed citations

6.

Scapicchio, Camilla, et al.. (2022). EXPLAINING THE BEHAVIOUR OF A CONVOLUTIONAL NEURAL NETWORK FOR BREAST DENSITY ASSESSMENT. Physica Medica. 104. S42–S42. 1 indexed citations

7.

Scapicchio, Camilla, Michela Gabelloni, Andrea Barucci, et al.. (2021). A deep look into radiomics. La radiologia medica. 126(10). 1296–1311. 259 indexed citations breakdown →

8.

Scapicchio, Camilla, Michela Gabelloni, L. Cerdá Alberich, et al.. (2021). DICOM-MIABIS integration model for biobanks: a use case of the EU PRIMAGE project. European Radiology Experimental. 5(1). 20–20. 10 indexed citations

9.

Scapicchio, Camilla, et al.. (2021). Convolutional Neural Networks for Breast Density Classification: Performance and Explanation Insights. Applied Sciences. 12(1). 148–148. 10 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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