Sara Moccia
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 2%
- Biomedical Engineering top 10%
- Surgery top 10%
- Artificial Intelligence top 5%
- Co-authors
- Elena De MomiLeonardo S. MattosEmanuele FrontoniSara El HadjiMaria Chiara FiorentinoLucia MigliorelliGiorgio PerettiEnrico G. Caiani
- Topics
- Fetal and Pediatric Neurological Disorders (10 papers)Head and Neck Cancer Studies (10 papers)Voice and Speech Disorders (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- ItalySwitzerlandSpain
In The Last Decade
Sara Moccia
100 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Radiology, Nuclear Medicine and Imaging 684
- Computer Vision and Pattern Recognition 481
- Biomedical Engineering 453
- Surgery 356
- Artificial Intelligence 330
Countries citing papers authored by Sara Moccia
This map shows the geographic impact of Sara Moccia'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 Sara Moccia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Moccia more than expected).
Fields of papers citing papers by Sara Moccia
This network shows the impact of papers produced by Sara Moccia. 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 Sara Moccia. The network helps show where Sara Moccia may publish in the future.
Co-authorship network of co-authors of Sara Moccia
This figure shows the co-authorship network connecting the top 25 collaborators of Sara Moccia. A scholar is included among the top collaborators of Sara Moccia 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 Sara Moccia. Sara Moccia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 12 | |
| 3 | 11 | |
| 4 | 3 | |
| 5 | 21 | |
| 6 | 15 | |
| 7 | 12 | |
| 8 | 96 | |
| 9 | 24 | |
| 10 | 50 | |
| 11 | 9 | |
| 12 | 73 | |
| 13 | 19 | |
| 14 | 3 | |
| 15 | 11 | |
| 16 | FCNN-based segmentation of kidney vessels - Towards constraints definition for safe robot-assisted nephrectomy | 1 |
| 17 | 24 | |
| 18 | 1 | |
| 19 | Safety enhancement in robotic neurosurgery through vessel tracking | 1 |
| 20 | Vocal Folds Disorders Detection and Classification in Endoscopic Narrow-Band Images | 1 |
About Sara Moccia
Sara Moccia is a scholar working on Otorhinolaryngology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 106 papers that have together received 2.0k indexed citations. Recurring topics across this work include Fetal and Pediatric Neurological Disorders (10 papers), Head and Neck Cancer Studies (10 papers) and Voice and Speech Disorders (10 papers). The work is most often cited by research in Health Informatics (128 citations), Otorhinolaryngology (178 citations) and Radiology, Nuclear Medicine and Imaging (684 citations). Sara Moccia has collaborated with scholars based in Italy, Switzerland and Spain. Frequent co-authors include Elena De Momi, Leonardo S. Mattos, Emanuele Frontoni, Sara El Hadji, Maria Chiara Fiorentino, Lucia Migliorelli, Giorgio Peretti, Enrico G. Caiani, Gianluca Pontone and Mauro Pepi. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.