Chase Krumpelman

797 total citations
9 papers, 218 citations indexed

About

Chase Krumpelman is a scholar working on Molecular Biology, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Chase Krumpelman has authored 9 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Epidemiology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Chase Krumpelman's work include Meta-analysis and systematic reviews (2 papers), Acute Ischemic Stroke Management (2 papers) and Bioinformatics and Genomic Networks (2 papers). Chase Krumpelman is often cited by papers focused on Meta-analysis and systematic reviews (2 papers), Acute Ischemic Stroke Management (2 papers) and Bioinformatics and Genomic Networks (2 papers). Chase Krumpelman collaborates with scholars based in United States. Chase Krumpelman's co-authors include Joydeep Ghosh, Raymond J. Mooney, Arindam Banerjee, Sugato Basu, Edward M. Marcotte, Wankyu Kim, Thomas A. Kent, Pitchaiah Mandava, Santosh B. Murthy and Jharna N. Shah and has published in prestigious journals such as PLoS ONE, Stroke and Genome biology.

In The Last Decade

Chase Krumpelman

8 papers receiving 202 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chase Krumpelman United States	4	96	80	30	30	29	9	218
Beatriz Pontes Spain	8	138 1.4×	187 2.3×	42 1.4×	27 0.9×	27 0.9×	14	330
Walaa Gad Egypt	9	125 1.3×	51 0.6×	95 3.2×	32 1.1×	11 0.4×	42	264
Raúl Giráldez Spain	8	140 1.5×	188 2.4×	43 1.4×	24 0.8×	25 0.9×	15	325
Vassilis N. Ioannidis United States	8	155 1.6×	33 0.4×	16 0.5×	23 0.8×	12 0.4×	26	219
Guosheng Gu China	11	66 0.7×	142 1.8×	28 0.9×	118 3.9×	18 0.6×	38	345
Maria A. Tsiarli United States	5	96 1.0×	56 0.7×	33 1.1×	49 1.6×	34 1.2×	7	274
Mugizi Robert Rwebangira United States	6	138 1.4×	20 0.3×	34 1.1×	51 1.7×	17 0.6×	14	239
Taylor Cassidy United States	12	502 5.2×	61 0.8×	73 2.4×	36 1.2×	39 1.3×	21	550
Yoshitaka Kameya Japan	10	209 2.2×	21 0.3×	31 1.0×	13 0.4×	24 0.8×	34	278
Giannis Nikolentzos France	9	215 2.2×	52 0.7×	23 0.8×	71 2.4×	11 0.4×	17	281

Countries citing papers authored by Chase Krumpelman

Since Specialization

Citations

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

Fields of papers citing papers by Chase Krumpelman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chase Krumpelman

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

All Works

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9 of 9 papers shown

Gennaro, Nicolò, Amir A. Borhani, Linda C. Kelahan, et al.. (2025). Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer. Tomography. 11(3). 20–20.

Tang, Jianing, Chase Krumpelman, Jonathan J. Russin, et al.. (2024). Highly accelerated non‐contrast‐enhanced time‐resolved 4D MRA using stack‐of‐stars golden‐angle radial acquisition with a self‐calibrated low‐rank subspace reconstruction. Magnetic Resonance in Medicine. 93(2). 615–629. 1 indexed citations

Mandava, Pitchaiah, Chase Krumpelman, Jharna N. Shah, Donna L. White, & Thomas A. Kent. (2013). Quantification of Errors in Ordinal Outcome Scales Using Shannon Entropy: Effect on Sample Size Calculations. PLoS ONE. 8(7). e67754–e67754. 14 indexed citations

Mandava, Pitchaiah, et al.. (2012). Abstract 2374: A New More Sensitive Method to Assess Balance Among Stroke Trial Populations. Stroke. 43(suppl_1). 1 indexed citations

Mandava, Pitchaiah, Chase Krumpelman, Santosh B. Murthy, & Thomas A. Kent. (2012). A Critical Review of Stroke Trial Analytical Methodology: Outcome Measures, Study Design, and Correction for Imbalances. Translational Stroke Research. 833–861. 10 indexed citations

Krumpelman, Chase, Pitchaiah Mandava, & Thomas A. Kent. (2012). Abstract 2372: Error Rate Estimates for the modified Rankin Score “Shift Analysis” Using Information Theory Modeling. Stroke. 43(suppl_1). 1 indexed citations

Kim, Wankyu, Chase Krumpelman, & Edward M. Marcotte. (2008). Inferring mouse gene functions from genomic-scale data using a combined functional network/classification strategy. Genome biology. 9(S1). S5–S5. 60 indexed citations

Krumpelman, Chase & Joydeep Ghosh. (2007). Matching and Visualization of Multiple Overlapping Clusterings of Microarray Data. 121–126. 3 indexed citations

Banerjee, Arindam, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, & Raymond J. Mooney. (2005). Model-based overlapping clustering. 532–537. 128 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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