Benedetta Bracci

1.3k total citations · 1 hit paper
18 papers, 762 citations indexed

About

Benedetta Bracci is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Surgery. According to data from OpenAlex, Benedetta Bracci has authored 18 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Infectious Diseases and 4 papers in Surgery. Recurrent topics in Benedetta Bracci's work include Radiomics and Machine Learning in Medical Imaging (6 papers), COVID-19 Clinical Research Studies (5 papers) and COVID-19 diagnosis using AI (5 papers). Benedetta Bracci is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), COVID-19 Clinical Research Studies (5 papers) and COVID-19 diagnosis using AI (5 papers). Benedetta Bracci collaborates with scholars based in Italy, United States and Switzerland. Benedetta Bracci's co-authors include Michela Polici, Damiano Caruso, Andrea Laghi, Marta Zerunian, Gisella Guido, Tiziano Polidori, Francesco Pucciarelli, Carlotta Rucci, Chiara De Dominicis and Laura Andreozzi and has published in prestigious journals such as Journal of Bone and Joint Surgery, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Benedetta Bracci

17 papers receiving 744 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.

Chest CT Features of COVID-19 in Rome, Italy

2020 416 citations Damiano Caruso, Marta Zerunian et al. Radiology profile →

Peers

Benedetta Bracci

RNMI

PRM

ONCOL

Gisella Guido Italy

Tiziano Polidori Italy

Francesco Pucciarelli Italy

Yijie Fang China

Carlotta Rucci Italy

Kasey Halsey United States

Michela Polici Italy

Bram Geurts Netherlands

Soyeoun Lim South Korea

Chungao Li China

Gisella Guido Italy

Benedetta Bracci

555 ×1.1

RNMI

296 ×1.0

120 ×0.7

PRM

165 ×1.0

ONCOL

142 ×1.1

Citations per year, relative to Benedetta Bracci Benedetta Bracci (= 1×) peers Gisella Guido

Countries citing papers authored by Benedetta Bracci

Since Specialization

Citations

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

Fields of papers citing papers by Benedetta Bracci

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benedetta Bracci

This figure shows the co-authorship network connecting the top 25 collaborators of Benedetta Bracci. A scholar is included among the top collaborators of Benedetta Bracci 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 Benedetta Bracci. Benedetta Bracci 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:

18 of 18 papers shown

Vazquez, Oscar, et al.. (2024). Prevalence of Complications Due to Transphyseal Hematogenous Osteomyelitis. Journal of Bone and Joint Surgery. 107(3). e7–e7.

Polidori, Tiziano, Domenico De Santis, Carlotta Rucci, et al.. (2023). Radiomics applications in cardiac imaging: a comprehensive review. La radiologia medica. 128(8). 922–933. 28 indexed citations

Zerunian, Marta, Francesco Pucciarelli, Michela Polici, et al.. (2022). Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review. BioMed Research International. 2022(1). 1147111–1147111. 4 indexed citations

Bracci, Benedetta, Domenico De Santis, Mariarita Tarallo, et al.. (2022). Adrenal Lesions: A Review of Imaging. Diagnostics. 12(9). 2171–2171. 7 indexed citations

Caruso, Damiano, Marta Zerunian, Michela Polici, et al.. (2022). Diagnostic performance of CT lung severity score and quantitative chest CT for stratification of COVID-19 patients. La radiologia medica. 127(3). 309–317. 8 indexed citations

Guido, Gisella, Michela Polici, Domenico De Santis, et al.. (2022). Iterative Reconstruction: State-of-the-Art and Future Perspectives. Journal of Computer Assisted Tomography. 47(2). 244–254. 11 indexed citations

Caruso, Damiano, Elisa Rosati, Marco Rengo, et al.. (2021). Optimization of contrast medium volume for abdominal CT in oncologic patients: prospective comparison between fixed and lean body weight-adapted dosing protocols. Insights into Imaging. 12(1). 40–40. 27 indexed citations

Caruso, Damiano, Francesco Pucciarelli, Marta Zerunian, et al.. (2021). Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia. La radiologia medica. 126(11). 1415–1424. 20 indexed citations

Caruso, Damiano, Marta Zerunian, Francesco Pucciarelli, et al.. (2021). Influence of Adaptive Statistical Iterative Reconstructions on CT Radiomic Features in Oncologic Patients. Diagnostics. 11(6). 1000–1000. 8 indexed citations

10.

Caruso, Damiano, Michela Polici, Marta Zerunian, et al.. (2021). Radiomics in Oncology, Part 2: Thoracic, Genito-Urinary, Breast, Neurological, Hematologic and Musculoskeletal Applications. Cancers. 13(11). 2681–2681. 25 indexed citations

11.

Caruso, Damiano, Marta Zerunian, Francesco Pucciarelli, et al.. (2021). Imaging of abdominal complications of COVID-19 infection. BJR|Open. 3(1). 20200052–20200052. 13 indexed citations

12.

Caruso, Damiano, Michela Polici, Marta Zerunian, et al.. (2021). Radiomics in Oncology, Part 1: Technical Principles and Gastrointestinal Application in CT and MRI. Cancers. 13(11). 2522–2522. 38 indexed citations

13.

Caruso, Damiano, Tiziano Polidori, Gisella Guido, et al.. (2020). Typical and atypical COVID-19 computed tomography findings. World Journal of Clinical Cases. 8(15). 3177–3187. 38 indexed citations

14.

Caruso, Damiano, Michela Polici, Marta Zerunian, et al.. (2020). Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients. La radiologia medica. 126(2). 243–249. 33 indexed citations

15.

Caruso, Damiano, Marta Zerunian, Michela Polici, et al.. (2020). Chest CT Features of COVID-19 in Rome, Italy. Radiology. 296(2). E79–E85. 416 indexed citations breakdown →

16.

Rigante, Donato, et al.. (2017). Handy Hints About Raynaud's Phenomenon in Children: A Critical Review. Pediatric Dermatology. 34(3). 235–239. 1 indexed citations

17.

Esposito, Susanna, et al.. (2016). Lung Involvement in Children with Hereditary Autoinflammatory Disorders. International Journal of Molecular Sciences. 17(12). 2111–2111. 21 indexed citations

18.

Rigante, Donato, et al.. (2016). Critical Overview of the Risk Scoring Systems to Predict Non-Responsiveness to Intravenous Immunoglobulin in Kawasaki Syndrome. International Journal of Molecular Sciences. 17(3). 278–278. 64 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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