V. Parisi

59 papers receiving 1.0k citations

Peers

V. Parisi
Comparison fields: 5 of 132
  • Numerical Analysis 94
  • Hepatology 93
  • Computational Theory and Mathematics 124
  • Oncology 187
  • Artificial Intelligence 140
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Liming Wu China
Rehan Ali United States
Marcel Schilling Germany
Claus Bendtsen United Kingdom
J. W. Goodman United States
Shih-Ho Wang Taiwan
Weijiang Zhang China
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Citations per year

Countries citing papers authored by V. Parisi

Since Specialization
Citations

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

Fields of papers citing papers by V. Parisi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside V. Parisi, 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 V. Parisi Line = papers co-authored together V. Parisi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1985170
2
18F-FDG PET is an early predictor of pathologic tumor response to preoperative radiochemotherapy in locally advanced rectal cancer.
2006162
3 199857
4
Detection of circulating tumor cells in carcinoma patients by a novel epidermal growth factor receptor reverse transcription-PCR assay.
200057
5 199550
6 200345
7 197938
8 202333
9 200632
10 200732
11 200726
12
Thromboelastographic profiles as a tool for thrombotic risk in digestive tract cancer.
200726
13 199926
14 198825
15 199317
16 200417
17 200216
18 200316
19 198416
20 198416

About V. Parisi

V. Parisi is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Electrical and Electronic Engineering, Oncology and Materials Chemistry, having authored 61 papers that have together received 1.1k indexed citations. Recurring topics across this work include Thin-Film Transistor Technologies (7 papers), Gastric Cancer Management and Outcomes (6 papers), Silicon Nanostructures and Photoluminescence (5 papers), Advanced Optimization Algorithms Research (4 papers), Colorectal Cancer Treatments and Studies (4 papers), Diamond and Carbon-based Materials Research (4 papers), Colorectal Cancer Surgical Treatments (4 papers) and Colorectal and Anal Carcinomas (3 papers). The work is most often cited by research in Numerical Analysis (94 citations), Hepatology (93 citations), Computational Theory and Mathematics (124 citations), Oncology (187 citations) and Artificial Intelligence (140 citations). V. Parisi has collaborated with scholars based in Italy, United States and Malaysia. Frequent co-authors include Filippo Aluffi-Pentini, Francesco Zirilli, F. Cremona, Paolo Delrio, Francesco Izzo, Raffaéle Palaia, Steven A. Curley, Giuseppe Lucio Cascini, Secondo Lastoria and Fabiana Tatangelo. Their work appears in journals such as ACM Transactions on Mathematical Software, Applied Surface Science, Journal of Theoretical Biology, Journal of Chemotherapy and Annals of Surgery.

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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