Pasqualino Favoriti

14 papers and 652 indexed citations i.

About

Pasqualino Favoriti is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Pasqualino Favoriti has authored 14 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Surgery, 4 papers in Endocrinology, Diabetes and Metabolism and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Pasqualino Favoriti’s work include Thyroid Cancer Diagnosis and Treatment (4 papers), Thyroid and Parathyroid Surgery (2 papers) and Vascular Malformations and Hemangiomas (1 paper). Pasqualino Favoriti is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (4 papers), Thyroid and Parathyroid Surgery (2 papers) and Vascular Malformations and Hemangiomas (1 paper). Pasqualino Favoriti collaborates with scholars based in Italy. Pasqualino Favoriti's co-authors include Francesco Corcione, Gabriele Carbone, Felice Pirozzi, Marco Greco, Raffaele Pirozzi, Giuseppe Pisano, Pietro Giorgio Calò, Angelo Nicolosi, Alberto Tatti and Salvatore Sorrenti and has published in prestigious journals such as International Journal of Molecular Sciences, Aging Clinical and Experimental Research and International Journal of Surgery.

In The Last Decade

Co-authorship network of co-authors of Pasqualino Favoriti i

Fields of papers citing papers by Pasqualino Favoriti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Pasqualino Favoriti

Since Specialization
Citations

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

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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2025