William Barcella

19 total papers · 925 total citations
10 papers, 209 citations indexed

About

William Barcella is a scholar working on Statistics and Probability, Artificial Intelligence and Urology. According to data from OpenAlex, William Barcella has authored 10 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 5 papers in Artificial Intelligence and 2 papers in Urology. Recurrent topics in William Barcella's work include Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (4 papers) and Statistical Methods and Bayesian Inference (3 papers). William Barcella is often cited by papers focused on Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (4 papers) and Statistical Methods and Bayesian Inference (3 papers). William Barcella collaborates with scholars based in United Kingdom, United States and Italy. William Barcella's co-authors include Maria De Iorio, James Malone‐Lee, Gianluca Baio, Marianna Fontana, Jennifer A. Steeden, Vivek Muthurangu, Carol Whelan, Helen J. Lachmann, Philip N. Hawkins and Ana Martinez–Naharro and has published in prestigious journals such as Statistics in Medicine, JACC. Cardiovascular imaging and Journal of the Royal Statistical Society Series C (Applied Statistics).

In The Last Decade

William Barcella

10 papers receiving 205 citations

Author Peers

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

Author						Papers	Cites
William Barcella	110	62	52	48	43	10	209
Xianghong Hu	82 0.7×	4 0.1×	17 0.3×	19 0.4×	33 0.8×	7	251
Jingsi Ming	109 1.0×	4 0.1×	16 0.3×	17 0.4×	29 0.7×	11	235
M. Zacchero	126 1.1×	21 0.3×	5 0.1×	18 0.4×	18 0.4×	12	260
Anne-Cécile Huby	98 0.9×	42 0.7×	90 1.7×	11 0.2×	15 0.3×	14	240
Ben Omega Petrazzini	51 0.5×	5 0.1×	55 1.1×	7 0.1×	21 0.5×	18	246
Claire Trivin	42 0.4×	65 1.0×	18 0.3×	10 0.2×	15 0.3×	7	212
Leping Shao	31 0.3×	97 1.6×	44 0.8×	20 0.4×	91 2.1×	10	261
J. Rahman	180 1.6×	99 1.6×	94 1.8×	38 0.8×	32 0.7×	9	249
Brendan Wisniowski	111 1.0×	62 1.0×	38 0.7×	29 0.6×	13 0.3×	11	192
Sarah Seiler-Mußler	24 0.2×	98 1.6×	52 1.0×	9 0.2×	11 0.3×	13	212

Countries citing papers authored by William Barcella

Since Specialization

Citations

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

Fields of papers citing papers by William Barcella

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Barcella

This figure shows the co-authorship network connecting the top 25 collaborators of William Barcella. A scholar is included among the top collaborators of William Barcella 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 William Barcella. William Barcella 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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