John G. Pearce

52 total papers · 600 total citations
33 papers, 476 citations indexed

About

John G. Pearce is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Control and Systems Engineering. According to data from OpenAlex, John G. Pearce has authored 33 papers receiving a total of 476 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Ophthalmology and 5 papers in Control and Systems Engineering. Recurrent topics in John G. Pearce's work include Simulation Techniques and Applications (4 papers), AI in cancer detection (3 papers) and Antibiotics Pharmacokinetics and Efficacy (3 papers). John G. Pearce is often cited by papers focused on Simulation Techniques and Applications (4 papers), AI in cancer detection (3 papers) and Antibiotics Pharmacokinetics and Efficacy (3 papers). John G. Pearce collaborates with scholars based in United States, Australia and United Kingdom. John G. Pearce's co-authors include Yuri R. Parisky, Giske Ursin, Darcy Spicer, Malcolm C. Pike, Ted Maddess, Norman L. Patt, John R. Daniels, Melvin A. Astrahan, Andy Pike and Donna Shoupe and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, Radiology and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

John G. Pearce

31 papers receiving 455 citations

Author Peers

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

Author						Papers	Cites
John G. Pearce	220	204	110	100	98	33	476
Yasunari Tsuchihashi	102 0.5×	72 0.4×	55 0.5×	78 0.8×	28 0.3×	43	480
Kristin Johnson	246 1.1×	116 0.6×	164 1.5×	161 1.6×	51 0.5×	22	430
Rama R. Gullapalli	73 0.3×	88 0.4×	71 0.6×	69 0.7×	91 0.9×	23	449
Richard N. Eisen	169 0.8×	189 0.9×	22 0.2×	52 0.5×	87 0.9×	26	552
Jun Zhang	134 0.6×	228 1.1×	41 0.4×	133 1.3×	28 0.3×	24	458
Federica Corso	84 0.4×	129 0.6×	20 0.2×	81 0.8×	87 0.9×	24	444
André Grivegnee	75 0.3×	154 0.8×	99 0.9×	83 0.8×	14 0.1×	27	537
Gareth Irwin	77 0.3×	167 0.8×	54 0.5×	53 0.5×	121 1.2×	27	488
M. E. De Ferrari	82 0.4×	114 0.6×	9 0.1×	180 1.8×	98 1.0×	26	511
Yijun Wu	131 0.6×	92 0.5×	41 0.4×	142 1.4×	66 0.7×	69	543

Countries citing papers authored by John G. Pearce

Since Specialization

Citations

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

Fields of papers citing papers by John G. Pearce

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Pearce. 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 John G. Pearce. The network helps show where John G. Pearce may publish in the future.

Co-authorship network of co-authors of John G. Pearce

This figure shows the co-authorship network connecting the top 25 collaborators of John G. Pearce. A scholar is included among the top collaborators of John G. Pearce 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 John G. Pearce. John G. Pearce 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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