Ricard Masia

3.6k citations
72 papers · 2.2k indexed · 1 hit paper · h-index 27
Topics
Liver Disease Diagnosis and Treatment (17 papers)Cardiac Ischemia and Reperfusion (9 papers)Liver Disease and Transplantation (8 papers)

In The Last Decade

Ricard Masia

70 papers receiving 2.2k citations

Hit Papers

Hepatocyte TAZ/WWTR1 Promotes Inflammation and Fibrosis i...20162026201920222016100200300

Peers

Ricard Masia
Comparison fields: 5 of 103
  • Epidemiology 817
  • Molecular Biology 603
  • Hepatology 432
  • Pathology and Forensic Medicine 372
  • Surgery 370
Replace Shinya Sato with:
Shinya Sato Japan
Pamela L. Tuma United States
Ning Xu Sweden
Albert Mennone United States
Minoru Okuma Japan
Yasuyuki Okamoto Japan
Shinji Iwasaki Japan
Keiji Hirata Japan
Isao Okazaki Japan
Anna Moles Spain
Ricard Masia relative to Shinya Sato Japan Shinya Sato's profile →
Citations per field
00.5×1.5×2.0×
Shinya Sato · 1×
Citations per year

Countries citing papers authored by Ricard Masia

Since Specialization
Citations

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

Fields of papers citing papers by Ricard Masia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ricard Masia

This figure shows the co-authorship network connecting the top 25 collaborators of Ricard Masia. A scholar is included among the top collaborators of Ricard Masia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ricard Masia. Ricard Masia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 46
4 48
5 2
6 4
7 69
8 142
9 15
10 36
11 6
12 2
13 4
14 11
15 1
16 9
17 1
18 0
19 24
20 11

About Ricard Masia

Ricard Masia is a scholar working on Hepatology, Pathology and Forensic Medicine and Epidemiology, having authored 72 papers that have together received 2.2k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (17 papers), Cardiac Ischemia and Reperfusion (9 papers) and Liver Disease and Transplantation (8 papers). The work is most often cited by research in Hepatology (432 citations), Epidemiology (817 citations) and Pathology and Forensic Medicine (372 citations). Ricard Masia has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Kathleen E. Corey, Colin G. Nichols, Raymond T. Chung, Gregory Y. Lauwers, Stephanie A. Osganian, Tracey G. Simon, Jacqueline B. Henson, Klaus W. Beyenbach, Jonathan Chen and Maryam Kherad Pezhouh. Their work appears in journals such as Nature, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

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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