Colin B. Compas

1.9k total citations · 1 hit paper
15 papers, 618 citations indexed

About

Colin B. Compas is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Colin B. Compas has authored 15 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Colin B. Compas's work include Medical Image Segmentation Techniques (7 papers), Ultrasound Imaging and Elastography (7 papers) and Cardiac Valve Diseases and Treatments (5 papers). Colin B. Compas is often cited by papers focused on Medical Image Segmentation Techniques (7 papers), Ultrasound Imaging and Elastography (7 papers) and Cardiac Valve Diseases and Treatments (5 papers). Colin B. Compas collaborates with scholars based in United States, Australia and Taiwan. Colin B. Compas's co-authors include Xi Yang, Cheryl Martin, Yonghui Wu, Kaleb E Smith, Christopher A. Harle, Tanja Magoč, Ying Zhang, Christopher Parisien, Anthony Costa and Gloria Lipori and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Medical Imaging and Medical Image Analysis.

In The Last Decade

Colin B. Compas

15 papers receiving 602 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.

A large language model for electronic health records

2022 434 citations Xi Yang, Aokun Chen et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Colin B. Compas United States	7	262	190	182	99	75	15	618
Yikuan Li United States	11	315 1.2×	123 0.6×	110 0.6×	45 0.5×	76 1.0×	21	606
Gregory Patrick Veldhuizen Germany	11	349 1.3×	292 1.5×	350 1.9×	32 0.3×	55 0.7×	24	784
Saeed Seyyedi Germany	5	205 0.8×	226 1.2×	76 0.4×	24 0.2×	30 0.4×	12	503
Pranavsingh Dhunnoo Ireland	4	210 0.8×	253 1.3×	400 2.2×	35 0.4×	29 0.4×	7	673
Malek Hammou Norway	3	133 0.5×	107 0.6×	64 0.4×	27 0.3×	34 0.5×	5	473
Michelle Livne Germany	10	161 0.6×	205 1.1×	102 0.6×	34 0.3×	25 0.3×	17	702
Khalid Gaffer Mohamed Saudi Arabia	6	164 0.6×	146 0.8×	152 0.8×	21 0.2×	59 0.8×	9	587
Rayan Krishnan United States	3	157 0.6×	123 0.6×	64 0.4×	26 0.3×	40 0.5×	3	385
Víctor M. Campello Spain	10	74 0.3×	231 1.2×	58 0.3×	110 1.1×	24 0.3×	24	441

Countries citing papers authored by Colin B. Compas

Since Specialization

Citations

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

Fields of papers citing papers by Colin B. Compas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Colin B. Compas. 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 Colin B. Compas. The network helps show where Colin B. Compas may publish in the future.

Co-authorship network of co-authors of Colin B. Compas

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

All Works

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15 of 15 papers shown

Yang, Jai‐Sing, et al.. (2024). Predicting blood–brain barrier permeability of molecules with a large language model and machine learning. Scientific Reports. 14(1). 15844–15844. 21 indexed citations

Yang, Xi, Aokun Chen, Kaleb E Smith, et al.. (2022). A large language model for electronic health records. npj Digital Medicine. 5(1). 194–194. 434 indexed citations breakdown →

Compas, Colin B., Ben A. Lin, Smita Sampath, et al.. (2015). Sparsity and Biomechanics Inspired Integration of Shape and Speckle Tracking for Cardiac Deformation Analysis. Lecture notes in computer science. 9126. 57–64. 6 indexed citations

Xie, Long, Suman Sedai, Xi Liang, et al.. (2015). Multi-atlas label fusion with augmented atlases for fast and accurate segmentation of cardiac MR images. 376–379. 5 indexed citations

Compas, Colin B., Tanveer Syeda-Mahmood, Patrick McNeillie, & David Beymer. (2014). Automatic detection of coronary stenosis in X-ray angiography through spatio-temporal tracking. 1299–1302. 15 indexed citations

Syeda-Mahmood, Tanveer, et al.. (2014). Discriminating normal and abnormal left ventricular shapes in four-chamber view 2D echocardiography. 15. 401–404. 5 indexed citations

Wong, Emily, Matthew O’Donnell, Colin B. Compas, et al.. (2014). Phase rotation in correlation coefficient filtering and multi-pass methods for 3-D speckle tracking in 4-D echocardiography. 1–4. 1 indexed citations

Compas, Colin B., Emily Wong, Smita Sampath, et al.. (2014). Radial Basis Functions for Combining Shape and Speckle Tracking in 4D Echocardiography. IEEE Transactions on Medical Imaging. 33(6). 1275–1289. 23 indexed citations

Dione, Donald P., Colin B. Compas, Xenophon Papademetris, et al.. (2013). Contour tracking in echocardiographic sequences via sparse representation and dictionary learning. Medical Image Analysis. 18(2). 253–271. 69 indexed citations

10.

Wong, Emily, Matthew O’Donnell, Karl Thiele, et al.. (2013). 4-D echocardiography assessment of local myocardial strain using 3-D speckle tracking combined with shape tracking. 100–103. 2 indexed citations

11.

Dione, Donald P., Colin B. Compas, Xenophon Papademetris, et al.. (2012). A Dynamical Appearance Model Based on Multiscale Sparse Representation: Segmentation of the Left Ventricle from 4D Echocardiography. Lecture notes in computer science. 15(Pt 3). 58–65. 10 indexed citations

12.

Huang, Xiaojie, Ben A. Lin, Colin B. Compas, et al.. (2012). Segmentation of left ventricles from echocardiographic sequences via sparse appearance representation. 305–312. 15 indexed citations

13.

Compas, Colin B., Emily Wong, Xiaojie Huang, et al.. (2012). A combined shape tracking and speckle tracking approach for 4D deformation analysis in echocardiography. 8. 458–461. 3 indexed citations

14.

Compas, Colin B., Ben A. Lin, Smita Sampath, et al.. (2011). Comparing Shape Tracking, Speckle Tracking, and a Combined Method for Deformation Analysis in Echocardiography. 4. 120–125. 5 indexed citations

15.

Compas, Colin B., Ben A. Lin, Smita Sampath, Albert J. Sinusas, & James S. Duncan. (2011). Combining shape and speckle tracking for deformation analysis in echocardiography using radial basis functions. 4. 1322–1325. 4 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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