Pol Servián

418 citations
37 papers · 307 · h-index 9

Impact in

Papers in

Pol Servián

32 papers receiving 303 citations

Peers

Pol Servián
Comparison fields: 5 of 37
  • Pulmonary and Respiratory Medicine 206
  • Urology 14
  • Obstetrics and Gynecology 15
  • Health Informatics 3
  • Rheumatology 29
Replace Gautum Agarwal with:
Gautum Agarwal United States
Marco Rosso Italy
Daniel Benamran Switzerland
Francesco Prata Italy
L.i-Ming Su United States
S. Dominique France
Alberto Ragusa Italy
Vivek Venkatramani United States
Pablo Gómez United States
Isuru Jayaratna United States
Pol Servián relative to Gautum Agarwal United States Gautum Agarwal's profile →
Citations per field
00.5×3.8×
Gautum Agarwal · 1×
Citations per year

Countries citing papers authored by Pol Servián

Since Specialization
Citations

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

Fields of papers citing papers by Pol Servián

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201847
2 201728
3 201927
4 202225
5 201623
6 201618
7 201517
8 201614
9 202213
10 20238
11 20138
12 20237
13 20197
14 20257
15 20236
16 20235
17 20215
18 20245
19 20135
20 20224

About Pol Servián

Pol Servián is a scholar working on Pulmonary and Respiratory Medicine, Rheumatology, Radiology, Nuclear Medicine and Imaging, Surgery and Molecular Biology, having authored 37 papers that have together received 307 indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (24 papers), Prostate Cancer Treatment and Research (16 papers), Urologic and reproductive health conditions (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), MRI in cancer diagnosis (3 papers), Kidney Stones and Urolithiasis Treatments (3 papers), Bladder and Urothelial Cancer Treatments (3 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (206 citations), Urology (14 citations), Obstetrics and Gynecology (15 citations), Health Informatics (3 citations) and Rheumatology (29 citations). Pol Servián has collaborated with scholars based in Spain, United Kingdom and France. Frequent co-authors include Juan Moróte, Silvia Proietti, Olivier Traxer, Esteban Emiliani, Michele Talso, Jacques Planas, A. Celma, Mohammed Baghdadi, J. Placer and Inés M. de Torres. Their work appears in journals such as Cancers, Urologic Oncology Seminars and Original Investigations, World Journal of Urology, The Journal of Urology and The Prostate.

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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