Sarah Mullin

34 total papers · 938 total citations
15 papers, 647 citations indexed

About

Sarah Mullin is a scholar working on Molecular Biology, Artificial Intelligence and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Sarah Mullin has authored 15 papers receiving a total of 647 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Artificial Intelligence and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Sarah Mullin's work include Biomedical Text Mining and Ontologies (4 papers), Machine Learning in Healthcare (2 papers) and Semantic Web and Ontologies (2 papers). Sarah Mullin is often cited by papers focused on Biomedical Text Mining and Ontologies (4 papers), Machine Learning in Healthcare (2 papers) and Semantic Web and Ontologies (2 papers). Sarah Mullin collaborates with scholars based in United States, Denmark and Australia. Sarah Mullin's co-authors include Michael B. Mock, Bernard Chaitman, Richard O. Russell, Ivar Ringqvist, George C. Kaiser, Thomas J. Ryan, Edwin L. Alderman, Nicholas T. Kouchoukos, Thomas Killip and Lloyd D. Fisher and has published in prestigious journals such as Circulation, Journal of Thoracic and Cardiovascular Surgery and Journal of Medical Internet Research.

In The Last Decade

Sarah Mullin

15 papers receiving 611 citations

Hit Papers

Survival of medically tre... 1982 2026 1996 2011 1982 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Sarah Mullin 426 410 238 59 38 15 647
Aryabod Razipour 474 1.1× 307 0.7× 219 0.9× 87 1.5× 45 1.2× 16 625
Gregory J Wehner 497 1.2× 259 0.6× 103 0.4× 44 0.7× 77 2.0× 27 686
J F McNeer 526 1.2× 396 1.0× 227 1.0× 34 0.6× 47 1.2× 9 722
Jacqueline Baras Shreibati 411 1.0× 256 0.6× 193 0.8× 185 3.1× 144 3.8× 20 776
Frank G. Aguilar 533 1.3× 215 0.5× 73 0.3× 17 0.3× 48 1.3× 15 654
Brian M. Kennelly 507 1.2× 208 0.5× 197 0.8× 28 0.5× 57 1.5× 21 593
Dorit Knappe 461 1.1× 88 0.2× 136 0.6× 110 1.9× 29 0.8× 26 591
Robert D. Rifkin 498 1.2× 370 0.9× 197 0.8× 94 1.6× 66 1.7× 30 736
M T Upton 655 1.5× 433 1.1× 111 0.5× 51 0.9× 62 1.6× 13 779
Stephanie C McLaughlin 541 1.3× 109 0.3× 117 0.5× 33 0.6× 54 1.4× 17 660

Countries citing papers authored by Sarah Mullin

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Mullin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarah Mullin

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