Daniela Terribile

74 papers receiving 923 citations

Peers

Daniela Terribile
Comparison fields: 5 of 66
  • Cancer Research 531
  • Pathology and Forensic Medicine 308
  • Surgery 469
  • Oncology 277
  • Radiology, Nuclear Medicine and Imaging 190
Replace Marguerite Bonaventura with:
Marguerite Bonaventura United States
José Roberto Filassi Brazil
Andrea M. Abbott United States
Richard Rainsbury United Kingdom
Ali Sever United Kingdom
Jamie L. Wagner United States
Audree B. Tadros United States
Lucio Fortunato Italy
A. Lisbona Canada
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Citations per year

Countries citing papers authored by Daniela Terribile

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Terribile

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Terribile, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniela Terribile Line = papers co-authored together Daniela Terribile links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005121
2 200669
3 201155
4 201242
5 201541
6 201436
7 202135
8 201030
9
Update on oncoplastic breast surgery.
201230
10
Conservative and radical oncoplastic approches in the surgical treatment of breast cancer.
200926
11 202124
12 202022
13 202221
14 201221
15 200820
16 200619
17 201219
18
The role of oxidized regenerate cellulose to prevent cosmetic defects in oncoplastic breast surgery.
201217
19 201916
20
Androgen receptor expression and outcome of neoadjuvant chemotherapy in triple-negative breast cancer
202115

About Daniela Terribile

Daniela Terribile is a scholar working on Cancer Research, Oncology, Surgery, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 77 papers that have together received 973 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (39 papers), Breast Implant and Reconstruction (24 papers), Breast Lesions and Carcinomas (24 papers), BRCA gene mutations in cancer (9 papers), MRI in cancer diagnosis (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Reconstructive Surgery and Microvascular Techniques (7 papers) and Cancer Treatment and Pharmacology (4 papers). The work is most often cited by research in Cancer Research (531 citations), Pathology and Forensic Medicine (308 citations), Surgery (469 citations), Oncology (277 citations) and Radiology, Nuclear Medicine and Imaging (190 citations). Daniela Terribile has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Riccardo Masetti, Gianluca Franceschini, Stefano Magno, Alba Di Leone, Paolo Belli, Marzia Salgarello, Luigia Nardone, Liliana Barone‐Adesi, Federica Chiesa and Antonino Mulè. Their work appears in journals such as The Breast Journal, Cancers, Journal of Personalized Medicine, Clinical Breast Cancer and The Breast.

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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