Evan D. Muse

5.6k total citations · 2 hit papers
54 papers, 3.8k citations indexed

About

Evan D. Muse is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Molecular Biology. According to data from OpenAlex, Evan D. Muse has authored 54 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cardiology and Cardiovascular Medicine, 12 papers in Surgery and 9 papers in Molecular Biology. Recurrent topics in Evan D. Muse's work include Adipokines, Inflammation, and Metabolic Diseases (7 papers), Regulation of Appetite and Obesity (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Evan D. Muse is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (7 papers), Regulation of Appetite and Obesity (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Evan D. Muse collaborates with scholars based in United States, Italy and Canada. Evan D. Muse's co-authors include Eric J. Topol, Steven R. Steinhubl, Luciano Rossetti, Philipp E. Scherer, Sanjay Bhanot, Brett P. Monia, Silvana Obici, Michael W. Rajala, Robert A. McKay and Seth S. Martin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and JAMA.

In The Last Decade

Evan D. Muse

53 papers receiving 3.7k citations

Hit Papers

The emerging field of mobile health 2015 2026 2018 2022 2015 2021 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Evan D. Muse United States 25 888 859 739 674 589 54 3.8k
Adam F. Cohen Netherlands 46 477 0.5× 943 1.1× 639 0.9× 1.4k 2.1× 292 0.5× 288 7.7k
Ulrike Grittner Germany 48 2.4k 2.7× 1.1k 1.3× 498 0.7× 675 1.0× 160 0.3× 260 7.4k
David Jarjoura United States 46 477 0.5× 862 1.0× 405 0.5× 2.5k 3.6× 387 0.7× 176 7.8k
José Luis Santos Chile 35 414 0.5× 1.1k 1.2× 236 0.3× 846 1.3× 331 0.6× 219 4.8k
Tjalf Ziemssen Germany 52 712 0.8× 562 0.7× 961 1.3× 1.6k 2.4× 195 0.3× 466 10.9k
Christopher Fry United Kingdom 46 816 0.9× 613 0.7× 1.7k 2.3× 1.3k 2.0× 638 1.1× 287 7.1k
Michael Chen United States 30 504 0.6× 561 0.7× 276 0.4× 585 0.9× 258 0.4× 135 4.2k
Wen‐Pin Chen Taiwan 38 352 0.4× 343 0.4× 355 0.5× 883 1.3× 154 0.3× 186 3.8k
Francesco Brigo Italy 49 1.0k 1.1× 528 0.6× 210 0.3× 494 0.7× 104 0.2× 409 8.4k
Donna L. White United States 32 1.9k 2.2× 771 0.9× 279 0.4× 733 1.1× 125 0.2× 112 5.0k

Countries citing papers authored by Evan D. Muse

Since Specialization
Citations

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

Fields of papers citing papers by Evan D. Muse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Evan D. Muse. 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 Evan D. Muse. The network helps show where Evan D. Muse may publish in the future.

Co-authorship network of co-authors of Evan D. Muse

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

All Works

20 of 20 papers shown
1.
Chen, Shang‐Fu, Sang Eun Lee, Hossein Javedani Sadaei, et al.. (2025). Meta-prediction of coronary artery disease risk. Nature Medicine. 31(7). 2277–2288. 1 indexed citations
2.
Epstein, Elizabeth, et al.. (2025). Apolipoprotein B outperforms low density lipoprotein particle number as a marker of cardiovascular risk in the UK Biobank. European Journal of Preventive Cardiology. 1 indexed citations
3.
Pandey, Amitabh C., et al.. (2024). AI-enhanced reconstruction of the 12-lead electrocardiogram via 3-leads with accurate clinical assessment. npj Digital Medicine. 7(1). 3 indexed citations
4.
Guglin, Maya, Mosi K. Bennett, Kunjan Bhatt, et al.. (2024). Misclassification of Pulmonary Hypertension With Current Hemodynamic Criteria. CHEST Journal. 167(1). 241–244. 1 indexed citations
5.
Muse, Evan D. & Eric J. Topol. (2024). Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management. Cell Metabolism. 36(4). 670–683. 15 indexed citations
6.
Bayoumy, Karim, Mohammed Gaber, Abdallah Elshafeey, et al.. (2021). Smart wearable devices in cardiovascular care: where we are and how to move forward. Nature Reviews Cardiology. 18(8). 581–599. 489 indexed citations breakdown →
7.
Bowman, Louise, Aris Baras, Robert M. Califf, et al.. (2020). Understanding the use of observational and randomized data in cardiovascular medicine. European Heart Journal. 41(27). 2571–2578. 21 indexed citations
8.
Muse, Evan D. & Eric J. Topol. (2019). Digital orthodoxy of human data collection. The Lancet. 394(10198). 556–556. 7 indexed citations
9.
Salfati, Elias, Emily Spencer, Sarah E. Topol, et al.. (2019). Re-analysis of whole-exome sequencing data uncovers novel diagnostic variants and improves molecular diagnostic yields for sudden death and idiopathic diseases. Genome Medicine. 11(1). 83–83. 49 indexed citations
10.
Muse, Evan D., Shan Yu, Chantle Edillor, et al.. (2018). Cell-specific discrimination of desmosterol and desmosterol mimetics confers selective regulation of LXR and SREBP in macrophages. Proceedings of the National Academy of Sciences. 115(20). E4680–E4689. 86 indexed citations
11.
Wineinger, Nathan E., et al.. (2018). Identification of paroxysmal atrial fibrillation subtypes in over 13,000 individuals. Heart Rhythm. 16(1). 26–30. 19 indexed citations
12.
Muse, Evan D., Ali Torkamani, & Eric J. Topol. (2018). When genomics goes digital. The Lancet. 391(10138). 2405–2405. 3 indexed citations
13.
Muse, Evan D., Haiying Wang, Paddy Barrett, et al.. (2017). A Whole Blood Molecular Signature for Acute Myocardial Infarction. Scientific Reports. 7(1). 59 indexed citations
14.
Muse, Evan D., Michael J. Blaha, Rajesh Tota-Maharaj, et al.. (2013). THE ASSOCIATION OF HUMAN RESISTIN AND CARDIOVASCULAR DISEASE IN THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA). Journal of the American College of Cardiology. 61(10). E1373–E1373. 1 indexed citations
16.
Muse, Evan D., Tony K.T. Lam, Philipp E. Scherer, & Luciano Rossetti. (2007). Hypothalamic resistin induces hepatic insulin resistance. Journal of Clinical Investigation. 117(6). 1670–1678. 92 indexed citations
17.
Buettner, Christoph, Rima Patel, Evan D. Muse, et al.. (2005). Severe impairment in liver insulin signaling fails to alter hepatic insulin action in conscious mice. Journal of Clinical Investigation. 115(5). 1306–1313. 43 indexed citations
18.
Muse, Evan D., Silvana Obici, Sanjay Bhanot, et al.. (2004). Role of resistin in diet-induced hepatic insulin resistance. Journal of Clinical Investigation. 114(2). 232–239. 280 indexed citations
19.
Muse, Evan D., Silvana Obici, Sanjay Bhanot, et al.. (2004). Role of resistin in diet-induced hepatic insulin resistance. Journal of Clinical Investigation. 114(2). 232–239. 273 indexed citations
20.
Jurevics, Helga, Janell Hostettler, Evan D. Muse, et al.. (2001). Cerebroside synthesis as a measure of the rate of remyelination following cuprizone‐induced demyelination in brain. Journal of Neurochemistry. 77(4). 1067–1076. 42 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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