Francisco Lopez‐Jimenez

1.8k total citations · 1 hit paper
62 papers, 1.0k citations indexed

About

Francisco Lopez‐Jimenez is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology and Physiology. According to data from OpenAlex, Francisco Lopez‐Jimenez has authored 62 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Cardiology and Cardiovascular Medicine, 10 papers in Epidemiology and 7 papers in Physiology. Recurrent topics in Francisco Lopez‐Jimenez's work include Cardiovascular Function and Risk Factors (13 papers), Cardiac Health and Mental Health (5 papers) and Heart Failure Treatment and Management (5 papers). Francisco Lopez‐Jimenez is often cited by papers focused on Cardiovascular Function and Risk Factors (13 papers), Cardiac Health and Mental Health (5 papers) and Heart Failure Treatment and Management (5 papers). Francisco Lopez‐Jimenez collaborates with scholars based in United States, United Kingdom and Czechia. Francisco Lopez‐Jimenez's co-authors include Virend K. Somers, M. Hassan Murad, Seema Kumar, Daniel Okorodudu, Marwan Jumean, Asma Javed, Ondřej Sochor, Zachi I. Attia, Paul A. Friedman and Patricia A. Pellikka and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Francisco Lopez‐Jimenez

51 papers receiving 1.0k 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.

Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: a systematic review and meta‐analysis

2014 349 citations M. Hassan Murad, Francisco Lopez‐Jimenez et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francisco Lopez‐Jimenez United States	15	374	319	258	115	107	62	1.0k
May C. M. Pian-Smith United States	18	235 0.6×	250 0.8×	274 1.1×	92 0.8×	133 1.2×	54	1.2k
Jennifer L. Wiltz United States	13	233 0.6×	275 0.9×	199 0.8×	239 2.1×	155 1.4×	26	1.3k
Capri G. Foy United States	18	519 1.4×	230 0.7×	275 1.1×	95 0.8×	148 1.4×	40	1.4k
Phyllis A. Richey United States	19	305 0.8×	244 0.8×	232 0.9×	55 0.5×	142 1.3×	49	927
Christopher W. Jones United States	23	137 0.4×	347 1.1×	138 0.5×	178 1.5×	203 1.9×	66	1.4k
Julio Álvarez‐Pitti Spain	19	382 1.0×	388 1.2×	197 0.8×	73 0.6×	132 1.2×	56	1.2k
Xin Zheng China	22	300 0.8×	123 0.4×	185 0.7×	66 0.6×	193 1.8×	76	1.2k
Raya Kheirbek United States	19	355 0.9×	248 0.8×	163 0.6×	98 0.9×	243 2.3×	52	984
Gregers S. Andersen Denmark	20	152 0.4×	315 1.0×	269 1.0×	178 1.5×	119 1.1×	78	1.4k
Cinzia Lo Noce Italy	17	277 0.7×	210 0.7×	71 0.3×	81 0.7×	73 0.7×	65	940

Countries citing papers authored by Francisco Lopez‐Jimenez

Since Specialization

Citations

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

Fields of papers citing papers by Francisco Lopez‐Jimenez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francisco Lopez‐Jimenez. 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 Francisco Lopez‐Jimenez. The network helps show where Francisco Lopez‐Jimenez may publish in the future.

Co-authorship network of co-authors of Francisco Lopez‐Jimenez

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wilsgaard, Tom, Wayne Rosamond, Henrik Schirmer, et al.. (2025). A New Biomarker of Aging Derived From Electrocardiograms Improves Risk Prediction of Incident Cardiovascular Disease. JACC Advances. 4(6). 101764–101764. 1 indexed citations

Jentzer, Jacob C., Ognjen Gajic, Vitaly Herasevich, et al.. (2025). Early prediction of shock in intensive care unit patients by machine learning using discrete electronic health record data. Journal of Critical Care. 88. 155093–155093. 1 indexed citations

Anjewierden, Scott, Zachi I. Attia, Francisco Lopez‐Jimenez, et al.. (2025). Artificial Intelligence–Derived Electrocardiographic Age Predicts Mortality in Adults With Congenital Heart Disease. JACC Advances. 4(6). 101777–101777. 2 indexed citations

Adedinsewo, Demilade, Patrick W. Johnson, Kathleen A. Young, et al.. (2024). Artificial intelligence–based screening for cardiomyopathy in an obstetric population: A pilot study. PubMed. 5(3). 132–140. 5 indexed citations

Muchtar, Eli, Francisco Lopez‐Jimenez, Zachi I. Attia, et al.. (2024). Predictors of Mortality by an Artificial Intelligence Enhanced Electrocardiogram Model for Cardiac Amyloidosis. ESC Heart Failure. 12(1). 677–682. 2 indexed citations

Lee, Hyoung-Ki, Francisco Lopez‐Jimenez, Gina K. Hesley, et al.. (2024). Estimation of In Vivo Human Carotid Artery Elasticity Using Arterial Dispersion Ultrasound Vibrometry. Ultrasound in Medicine & Biology. 51(2). 250–261.

Harmon, David, Christopher G. Scott, Dennis H. Murphree, et al.. (2023). Postdevelopment Performance and Validation of the Artificial Intelligence-Enhanced Electrocardiogram for Detection of Cardiac Amyloidosis. JACC Advances. 2(8). 100612–100612. 18 indexed citations

Klang, Eyal, et al.. (2023). Leveraging Large Language Models to Enhance Digital Health in Cardiology: A Preview of a Cutting-Edge Language Generation Model. SHILAP Revista de lepidopterología. 1(2). 105–108. 3 indexed citations

Adedinsewo, Demilade, Jennifer Dugan, Xiaoxi Yao, et al.. (2023). Screening for peripartum cardiomyopathies using artificial intelligence in Nigeria (SPEC-AI Nigeria): Clinical trial rationale and design. American Heart Journal. 261. 64–74. 9 indexed citations

10.

Shelly, Shahar, Francisco Lopez‐Jimenez, Michal Cohen‐Shelly, et al.. (2023). Accelerated Aging in LMNA Mutations Detected by Artificial Intelligence ECG–Derived Age. Mayo Clinic Proceedings. 98(4). 522–532. 8 indexed citations

11.

Akerman, Ashley P., Christopher G. Scott, Arian Beqiri, et al.. (2023). Automated Echocardiographic Detection of Heart Failure With Preserved Ejection Fraction Using Artificial Intelligence. JACC Advances. 2(6). 100452–100452. 46 indexed citations

12.

Jerome, Gerald J., William Boyer, Eduardo E. Bustamante, et al.. (2023). Increasing Equity of Physical Activity Promotion for Optimal Cardiovascular Health in Adults: A Scientific Statement From the American Heart Association. Circulation. 147(25). 1951–1962. 25 indexed citations

13.

Phelan, Jody, Zachi I. Attia, Ernest Diez Benavente, et al.. (2022). Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes. Scientific Reports. 12(1). 22625–22625. 16 indexed citations

14.

Rajai, Nazanin, José R. Medina‐Inojosa, M. Nyman, et al.. (2022). Abstract 13378: Association Between Social Connection and Biological Age as Determined by Artificial Intelligence-Enabled Electrocardiography. Circulation. 146(Suppl_1). 1 indexed citations

15.

Harmon, David, Demilade Adedinsewo, Matthew Johnson, et al.. (2022). Community-based participatory research application of an artificial intelligence-enhanced electrocardiogram for cardiovascular disease screening: A FAITH! Trial ancillary study. SHILAP Revista de lepidopterología. 12. 100431–100431. 10 indexed citations

16.

Muchtar, Eli, Surendra Dasari, Martha Grogan, et al.. (2022). Artificial Intelligence-Enhanced Models to Predict Light Chain Amyloidosis from Patients with Monoclonal Gammopathy of Undetermined Significance and Smoldering Multiple Myeloma. Blood. 140(Supplement 1). 7230–7232.

17.

Rmilah, Anan Abu, et al.. (2022). AN ARTIFICIAL INTELLIGENCE-ENABLED ECG FOR ASSESSING THE RISK OF LEFT VENTRICULAR DYSFUNCTION AMONG CANCER PATIENTS RECEIVING CHEMOTHERAPY. Journal of the American College of Cardiology. 79(9). 1932–1932. 3 indexed citations

18.

Csécs, Ibolya, J. Wells Askew, Francisco Lopez‐Jimenez, et al.. (2021). Mitigation of Aerosols Generated During Exercise Testing With a Portable High-Efficiency Particulate Air Filter With Fume Hood. CHEST Journal. 160(4). 1388–1396. 13 indexed citations

19.

Qian, Qi, et al.. (2010). ACEi/ARB for systolic heart failure: Closing the quality gap with a sustainable intervention at an academic medical center. Journal of Hospital Medicine. 6(3). 156–160. 15 indexed citations

20.

Fujiyoshi, Akira, M. Hassan Murad, Max Luna, et al.. (2010). Metabolic syndrome and its components are underdiagnosed in cardiology clinics. Journal of Evaluation in Clinical Practice. 17(1). 78–83. 11 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.

Explore authors with similar magnitude of impact