Francesco La Rosa
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- Multiple Sclerosis Research Studies 12
- Ophthalmology top 5%
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- Advanced Neuroimaging Techniques and Applications 6
- Neurology top 10%
- Epidemiology top 10%
- Multiple and Secondary Primary Cancers 11
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- Global Cancer Incidence and Screening 20
- Colorectal Cancer Screening and Detection 16
- Cancer Risks and Factors 6
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- Gaze Tracking and Assistive Technology 7
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- Breast Cancer Treatment Studies 6
Francesco La Rosa
103 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 136
- Pathology and Forensic Medicine 259
- Ophthalmology 126
- Radiology, Nuclear Medicine and Imaging 280
- Neurology 184
- Epidemiology 398
Countries citing papers authored by Francesco La Rosa
This map shows the geographic impact of Francesco La Rosa'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 Francesco La Rosa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco La Rosa more than expected).
Fields of papers citing papers by Francesco La Rosa
This network shows the impact of papers produced by Francesco La Rosa. 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 Francesco La Rosa. The network helps show where Francesco La Rosa may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Francesco La Rosa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 6 | |
| 5 | 2022 | 34 | |
| 6 | 2021 | 82 | |
| 7 | 2021 | 4 | |
| 8 | 2020 | 43 | |
| 9 | 2019 | 4 | |
| 10 | A novel segmentation framework for uveal melanoma in magnetic resonance imaging based on class activation maps | 2019 | 3 |
| 11 | Differential diagnosis of multiple sclerosis with machine learning-based central vein sign recognition | 2018 | 1 |
| 12 | 2015 | 2 | |
| 13 | 2013 | 36 | |
| 14 | 2008 | 15 | |
| 15 | 2007 | 2 | |
| 16 | 2004 | 3 | |
| 17 | 2004 | 7 | |
| 18 | 1991 | 17 | |
| 19 | [Tobacco smoke and malignant tumors. Analysis by birth cohorts from 1875 to 1935]. | 1989 | 3 |
| 20 | 1988 | 9 |
About Francesco La Rosa
Francesco La Rosa is a scholar working on Human-Computer Interaction, Oncology and Pathology and Forensic Medicine, having authored 110 papers that have together received 1.5k indexed citations. Recurring topics across this work include Global Cancer Incidence and Screening (20 papers), Colorectal Cancer Screening and Detection (16 papers), Multiple Sclerosis Research Studies (12 papers), Multiple and Secondary Primary Cancers (11 papers), Gaze Tracking and Assistive Technology (7 papers), Breast Cancer Treatment Studies (6 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Cancer Risks and Factors (6 papers). The work is most often cited by research in Pathology and Forensic Medicine (259 citations), Ophthalmology (126 citations) and Radiology, Nuclear Medicine and Imaging (280 citations). Francesco La Rosa has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Emilio Duca, Stefano Ricci, Maria Grazia Celani, Rino Vitali, Silvia Orengo-Nania, Ron Gross, Enrico Righetti, Giancarlo Iannizzotto, Meritxell Bach Cuadra and Cristina Granziera.
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.