Nicholas Lucarelli
Impact in
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- Artificial Intelligence in Healthcare and Education
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- Chronic Kidney Disease and Diabetes
Papers in
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- AI in cancer detection 7
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- Chronic Kidney Disease and Diabetes 3
- Co-authors
- Pinaki Sarder (10 shared papers)Avi Z. Rosenberg (3 shared papers)Jarcy Zee (2 shared papers)Kyung Chul Moon (2 shared papers)Anindya S. Paul (2 shared papers)Seung Seok Han (1 shared paper)Michelle Wong (1 shared paper)Donghwan Yun (2 shared papers)
- Journals
- Clinical Journal of the American Society of Nephrology (1 paper)Journal of the American Society of Nephrology (1 paper)PubMed (6 papers)Kidney360 (1 paper)
- Partner nations
- United StatesSouth KoreaPortugal
In The Last Decade
Nicholas Lucarelli
9 papers receiving 22 citations
Peers
Comparison fields: 5 of 15
- Health Informatics 2
- Nephrology 3
- Transplantation 1
- Artificial Intelligence 10
- Radiology, Nuclear Medicine and Imaging 5
Countries citing papers authored by Nicholas Lucarelli
This map shows the geographic impact of Nicholas Lucarelli'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 Nicholas Lucarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Lucarelli more than expected).
Fields of papers citing papers by Nicholas Lucarelli
This network shows the impact of papers produced by Nicholas Lucarelli. 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 Nicholas Lucarelli. The network helps show where Nicholas Lucarelli may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicholas Lucarelli, 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 | 2023 | 8 | |
| 2 | 2023 | 3 | |
| 3 | 2024 | 3 | |
| 4 | 2022 | 2 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 1 | |
| 7 | 2021 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 1 | |
| 10 | 2024 | 0 |
About Nicholas Lucarelli
Nicholas Lucarelli is a scholar working on Artificial Intelligence, Nephrology, Oncology, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 10 papers that have together received 22 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Chronic Kidney Disease and Diabetes (3 papers), Cell Image Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Renal and Vascular Pathologies (2 papers), Pediatric Urology and Nephrology Studies (2 papers), Single-cell and spatial transcriptomics (2 papers) and Colorectal Cancer Screening and Detection (2 papers). The work is most often cited by research in Health Informatics (2 citations), Nephrology (3 citations), Transplantation (1 citation), Artificial Intelligence (10 citations) and Radiology, Nuclear Medicine and Imaging (5 citations). Nicholas Lucarelli has collaborated with scholars based in United States, South Korea and Portugal. Frequent co-authors include Pinaki Sarder, Avi Z. Rosenberg, Jarcy Zee, Kyung Chul Moon, Anindya S. Paul, Seung Seok Han, Michelle Wong, Donghwan Yun, Luís Rodrigues and Tezcan Ozrazgat‐Baslanti. Their work appears in journals such as Clinical Journal of the American Society of Nephrology, Journal of the American Society of Nephrology, PubMed and Kidney360.
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.