M.Á. Prieto Díaz

52 total papers · 503 total citations
30 papers, 276 citations indexed

About

M.Á. Prieto Díaz is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and General Health Professions. According to data from OpenAlex, M.Á. Prieto Díaz has authored 30 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cardiology and Cardiovascular Medicine, 7 papers in Endocrinology, Diabetes and Metabolism and 5 papers in General Health Professions. Recurrent topics in M.Á. Prieto Díaz's work include Blood Pressure and Hypertension Studies (18 papers), Cardiac Health and Mental Health (7 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers). M.Á. Prieto Díaz is often cited by papers focused on Blood Pressure and Hypertension Studies (18 papers), Cardiac Health and Mental Health (7 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers). M.Á. Prieto Díaz collaborates with scholars based in Spain, United Kingdom and United States. M.Á. Prieto Díaz's co-authors include J.L. Llisterri, G.C. Rodríguez Roca, Sergio Cinza‐Sanjurjo, José Polo García, Alfonso Barquilla-García, May Azzawi, Hans Degens, J.A. Divisón, Vivencio Barrios and José R. Banegas and has published in prestigious journals such as Journal of Hypertension, Experimental Gerontology and Nitric Oxide.

In The Last Decade

M.Á. Prieto Díaz

25 papers receiving 269 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
M.Á. Prieto Díaz	169	57	56	35	35	30	276
Nieves Martell‐Claros	184 1.1×	53 0.9×	42 0.8×	30 0.9×	34 1.0×	29	320
Deepak Kamath	115 0.7×	38 0.7×	27 0.5×	41 1.2×	27 0.8×	22	293
Hilton Chaves	96 0.6×	45 0.8×	45 0.8×	23 0.7×	32 0.9×	21	306
Megan M. Clarke	165 1.0×	40 0.7×	51 0.9×	20 0.6×	22 0.6×	23	283
John S Dowden	190 1.1×	38 0.7×	56 1.0×	15 0.4×	45 1.3×	13	308
W.J. Elliott	114 0.7×	26 0.5×	23 0.4×	35 1.0×	39 1.1×	19	324
I Balažovjech	184 1.1×	73 1.3×	41 0.7×	10 0.3×	21 0.6×	27	257
Rosalinde K.E. Poortvliet	126 0.7×	41 0.7×	47 0.8×	30 0.9×	23 0.7×	14	314
Jingkuo Li	101 0.6×	83 1.5×	31 0.6×	33 0.9×	43 1.2×	27	332
Lina Matta	181 1.1×	24 0.4×	30 0.5×	28 0.8×	27 0.8×	24	303

Countries citing papers authored by M.Á. Prieto Díaz

Since Specialization

Citations

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

Fields of papers citing papers by M.Á. Prieto Díaz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.Á. Prieto Díaz. 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 M.Á. Prieto Díaz. The network helps show where M.Á. Prieto Díaz may publish in the future.

Co-authorship network of co-authors of M.Á. Prieto Díaz

This figure shows the co-authorship network connecting the top 25 collaborators of M.Á. Prieto Díaz. A scholar is included among the top collaborators of M.Á. Prieto Díaz 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 M.Á. Prieto Díaz. M.Á. Prieto Díaz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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