Chris J. Rose

1.2k total citations · 1 hit paper
14 papers, 802 citations indexed

About

Chris J. Rose is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Chris J. Rose has authored 14 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Pulmonary and Respiratory Medicine and 2 papers in Artificial Intelligence. Recurrent topics in Chris J. Rose's work include Radiomics and Machine Learning in Medical Imaging (7 papers), MRI in cancer diagnosis (6 papers) and Advanced MRI Techniques and Applications (3 papers). Chris J. Rose is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), MRI in cancer diagnosis (6 papers) and Advanced MRI Techniques and Applications (3 papers). Chris J. Rose collaborates with scholars based in United Kingdom, United States and Singapore. Chris J. Rose's co-authors include Geoff J.M. Parker, James P.B. O’Connor, Alan Jackson, Richard A.D. Carano, John C. Waterton, Caleb Roberts, Yvonne Watson, Giovanni A. Buonaccorsi, Samantha J. Mills and Susan Cheung and has published in prestigious journals such as Radiology, Clinical Cancer Research and British Journal of Cancer.

In The Last Decade

Chris J. Rose

14 papers receiving 798 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome

2014 495 citations James P.B. O’Connor, Chris J. Rose et al. Clinical Cancer Research profile →

Peers

Chris J. Rose

RNMI

PRM

ONCOL

S Chaudhari United States

Hailiang Li China

Amy N. Melsaether United States

Laurence Champion France

Michal R. Tomaszewski United States

Susan Cheung United Kingdom

Jesper Folsted Kallehauge Denmark

James A. d’Arcy United Kingdom

Claudio Spick Austria

Damiënne Marcus Netherlands

S Chaudhari United States

Chris J. Rose

516 ×0.8

RNMI

200 ×1.4

PRM

122 ×1.0

89 ×0.8

64 ×0.6

ONCOL

Citations per year, relative to Chris J. Rose Chris J. Rose (= 1×) peers S Chaudhari

Countries citing papers authored by Chris J. Rose

Since Specialization

Citations

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

Fields of papers citing papers by Chris J. Rose

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chris J. Rose. 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 Chris J. Rose. The network helps show where Chris J. Rose may publish in the future.

Co-authorship network of co-authors of Chris J. Rose

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

All Works

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14 of 14 papers shown

Karvellas, Constantine, Albert Salehi, Jaime L. Speiser, et al.. (2020). O9 Redefining poor prognostic criteria for acetaminophen-induced acute liver failure using regeneration and cell-death linked miRNA signatures. Abstracts. A5.1–A5. 1 indexed citations

Dickie, Ben, Chris J. Rose, Lucy Kershaw, et al.. (2017). The prognostic value of dynamic contrast-enhanced MRI contrast agent transfer constant Ktrans in cervical cancer is explained by plasma flow rather than vessel permeability. British Journal of Cancer. 116(11). 1436–1443. 27 indexed citations

Mansfield, James, Zena Salih, Lia P. Menasce, et al.. (2015). Automated prognostic pattern detection shows favourable diffuse pattern of FOXP3+ Tregs in follicular lymphoma. British Journal of Cancer. 113(8). 1197–1205. 14 indexed citations

Dickie, Ben, Lucy Kershaw, Andrew McPartlin, et al.. (2015). Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data. Magnetic Resonance in Medicine. 76(4). 1270–1281. 10 indexed citations

O’Connor, James P.B., Chris J. Rose, John C. Waterton, et al.. (2014). Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome. Clinical Cancer Research. 21(2). 249–257. 495 indexed citations breakdown →

Rose, Chris J., et al.. (2013). A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers. Journal of Pathology Informatics. 4(2). 4–4. 11 indexed citations

Rose, Chris J., James P.B. O’Connor, T.F. Cootes, et al.. (2013). Indexed distribution analysis for improved significance testing of spatially heterogeneous parameter maps: Application to dynamic contrast‐enhanced MRI biomarkers. Magnetic Resonance in Medicine. 71(3). 1299–1311. 6 indexed citations

Rose, Chris J., Samantha J. Mills, James P.B. O’Connor, et al.. (2009). Quantifying spatial heterogeneity in dynamic contrast‐enhanced MRI parameter maps. Magnetic Resonance in Medicine. 62(2). 488–499. 107 indexed citations

Mills, Samantha J., Calvin Soh, James P.B. O’Connor, et al.. (2009). Tumour enhancing fraction (EnF) in glioma: relationship to tumour grade. European Radiology. 19(6). 1489–1498. 14 indexed citations

10.

Roberts, Caleb, Geoff J.M. Parker, Chris J. Rose, et al.. (2008). Glandular Function in Sjögren Syndrome: Assessment with Dynamic Contrast-enhanced MR Imaging and Tracer Kinetic Modeling—Initial Experience. Radiology. 246(3). 845–853. 23 indexed citations

11.

O’Connor, James P.B., Alan Jackson, Giovanni A. Buonaccorsi, et al.. (2007). Organ‐specific effects of oxygen and carbogen gas inhalation on tissue longitudinal relaxation times. Magnetic Resonance in Medicine. 58(3). 490–496. 73 indexed citations

12.

O’Connor, James P.B., Gordon C. Jayson, Alan Jackson, et al.. (2007). Enhancing Fraction Predicts Clinical Outcome following First-Line Chemotherapy in Patients with Epithelial Ovarian Carcinoma. Clinical Cancer Research. 13(20). 6130–6135. 18 indexed citations

13.

Astley, Susan, Michael Brady, Chris J. Rose, & Reyer Zwiggelaar. (2006). Digital Mammography: 8th International Workshop, IWDM 2006, Manchester, UK, June 18-21, 2006, Proceedings (Lecture Notes in Computer Science). 1 indexed citations

14.

Astley, Susan, Michael Brady, Chris J. Rose, & Reyer Zwiggelaar. (2006). Proceedings of the 8th international conference on Digital Mammography. 2 indexed citations

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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