Jim Parr

601 total citations
11 papers, 474 citations indexed

About

Jim Parr is a scholar working on Computational Theory and Mathematics, Surgery and Management Science and Operations Research. According to data from OpenAlex, Jim Parr has authored 11 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computational Theory and Mathematics, 3 papers in Surgery and 3 papers in Management Science and Operations Research. Recurrent topics in Jim Parr's work include Advanced Multi-Objective Optimization Algorithms (4 papers), Probabilistic and Robust Engineering Design (3 papers) and Optimal Experimental Design Methods (3 papers). Jim Parr is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (4 papers), Probabilistic and Robust Engineering Design (3 papers) and Optimal Experimental Design Methods (3 papers). Jim Parr collaborates with scholars based in United Kingdom, India and United States. Jim Parr's co-authors include Alexander I. J. Forrester, Carren Holden, Andy J. Keane, Mahmoud Rowshandeli, Ian Forster, Dave Higgs, B.S. Dosanjh, Ammar Al‐Chalabi, Luis Garcia‐Gancedo and Arseniy Lavrov and has published in prestigious journals such as Aquaculture, Veterinary Record and JMIR mhealth and uhealth.

In The Last Decade

Jim Parr

11 papers receiving 441 citations

Peers

Countries citing papers authored by Jim Parr

Since Specialization

Citations

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

Fields of papers citing papers by Jim Parr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jim Parr

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

All Works

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11 of 11 papers shown

#	Work	Indexed citations
1	Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning Model 2025 ·Cureus ·Jim Parr, (unknown), (unknown), A. C. McLaren, Carl Deirmengian, (unknown)	1
2	Achieving High Accuracy in Predicting the Probability of Periprosthetic Joint Infection From Synovial Fluid in Patients Undergoing Hip or Knee Arthroplasty: The Development and Validation of a Multivariable Machine Learning Algorithm 2023 ·Cureus ·(unknown), (unknown), (unknown), Jim Parr, Eyal Kazin, A. C. McLaren, (unknown), Carl Deirmengian	6
3	A physiologically realistic virtual patient database for the study of arterial haemodynamics 2021 ·International Journal for Numerical Methods in Biomedical Engineering ·(unknown), Jim Parr, Perumal Nithiarasu, Sanjay Pant	12
4	The use of biotelemetry to explore disease progression markers in amyotrophic lateral sclerosis 2020 ·Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration ·(unknown), Arseniy Lavrov, Luis Garcia‐Gancedo, Jim Parr, Robert G. Hart, (unknown), Christopher E. Shaw, Ammar Al‐Chalabi, Rachael Marsden, Martin R. Turner, Kevin Talbot	17
5	Objectively Monitoring Amyotrophic Lateral Sclerosis Patient Symptoms During Clinical Trials With Sensors: Observational Study 2019 ·JMIR mhealth and uhealth ·Luis Garcia‐Gancedo, (unknown), Arseniy Lavrov, Jim Parr, R G Hart, Rachael Marsden, Martin R. Turner, Kevin Talbot, (unknown), Christopher E. Shaw, Ammar Al‐Chalabi	41
6	Enhancing infill sampling criteria for surrogate-based constrained optimization 2012 ·Journal of Computational Methods in Sciences and Engineering ·Jim Parr, Alexander I. J. Forrester, Andy J. Keane, Carren Holden	22
7	Handling Constraints in Surrogate-Based Optimization 2012 ·Jim Parr, Alexander I. J. Forrester, Andy J. Keane, Carren Holden	1
8	Infill sampling criteria for surrogate-based optimization with constraint handling 2012 ·Engineering Optimization ·Jim Parr, Andy J. Keane, Alexander I. J. Forrester, Carren Holden	155
9	Review of efficient surrogate infill sampling criteria with constraint handling 2010 ·ePrints Soton (University of Southampton) ·Jim Parr, Carren Holden, Alexander I. J. Forrester, Andy J. Keane	22
10	Potential for dietary phytase to improve the nutritive value of canola protein concentrate and decrease phosphorus output in rainbow trout (Oncorhynchus mykiss) held in 11°C fresh water 1999 ·Aquaculture ·Ian Forster, Dave Higgs, B.S. Dosanjh, Mahmoud Rowshandeli, Jim Parr	181
11	Chlamydiosis and abortion in a dairy herd 1994 ·Veterinary Record ·Andrew Holliman, Roger Daniel, Jim Parr, Peter C. Griffiths, (unknown), (unknown), R. Glyn Hewinson, M. Dawson, Ranald Munro	16

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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