World's Best Scientists 2026 revealed!

D-Index & Metrics

Medicine

D-Index
96
Citations
32312
World Ranking
9712
National Ranking
4998

Guido Germano publication distribution in Medicine in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Medicine in 2026. The highlighted bar marks where Guido Germano sits on this spectrum.

101–120 publications: 5 scientists 121–140 publications: 26 scientists 141–160 publications: 73 scientists 161–180 publications: 155 scientists 181–200 publications: 230 scientists 201–220 publications: 363 scientists 221–240 publications: 487 scientists 241–260 publications: 545 scientists 261–280 publications: 722 scientists 281–300 publications: 768 scientists 301–320 publications: 834 scientists 321–340 publications: 895 scientists 341–360 publications: 922 scientists 361–380 publications: 838 scientists 381–400 publications: 861 scientists 401–420 publications: 918 scientists 421–440 publications: 806 scientists 441–460 publications: 771 scientists 461–480 publications: 751 scientists 481–500 publications: 713 scientists 501–520 publications: 617 scientists 521–540 publications: 611 scientists 541–560 publications: 537 scientists 561–580 publications: 504 scientists 581–600 publications: 509 scientists 601–620 publications: 396 scientists 621–640 publications: 386 scientists 641–660 publications: 371 scientists 661–680 publications: 340 scientists 681–700 publications: 336 scientists 701–720 publications: 307 scientists 721–740 publications: 259 scientists 741–760 publications: 230 scientists 761–780 publications: 228 scientists 781–800 publications: 217 scientists 801–820 publications: 204 scientists 821–840 publications: 186 scientists 841–860 publications: 177 scientists 861–880 publications: 155 scientists 881–900 publications: 139 scientists 901–920 publications: 145 scientists 921–940 publications: 116 scientists 941–960 publications: 133 scientists 961–980 publications: 91 scientists 981–1,000 publications: 96 scientists 1,001–1,020 publications: 77 scientists 1,021–1,040 publications: 70 scientists 1,041–1,060 publications: 63 scientists 1,061–1,080 publications: 77 scientists 1,081–1,100 publications: 49 scientists 1,101–1,120 publications: 54 scientists 1,121–1,140 publications: 49 scientists 1,141–1,160 publications: 51 scientists 1,161–1,180 publications: 35 scientists 1,181–1,200 publications: 39 scientists 1,201–1,220 publications: 26 scientists 1,221–1,240 publications: 37 scientists 1,241–1,260 publications: 36 scientists 1,261–1,280 publications: 27 scientists 1,281–1,300 publications: 32 scientists 1,301–1,320 publications: 28 scientists 1,321–1,340 publications: 17 scientists 1,341–1,360 publications: 30 scientists 1,361–1,380 publications: 28 scientists 1,381–1,400 publications: 17 scientists 1,401–1,420 publications: 21 scientists 1,421–1,440 publications: 15 scientists 1,441–1,460 publications: 12 scientists 1,461–1,480 publications: 12 scientists 1,481–1,500 publications: 18 scientists 1,501–1,520 publications: 14 scientists 1,521–1,540 publications: 17 scientists 1,541–1,560 publications: 15 scientists 1,561–1,580 publications: 6 scientists 1,581–1,600 publications: 2 scientists 1,601–1,620 publications: 12 scientists 1,621–1,640 publications: 11 scientists 1,641–1,660 publications: 8 scientists 1,661–1,680 publications: 5 scientists 1,681–1,700 publications: 5 scientists 1,701–1,720 publications: 10 scientists 1,721–1,740 publications: 12 scientists 1,741–1,760 publications: 14 scientists 1,761–1,780 publications: 6 scientists 1,781–1,795 publications: 5 scientists 1,796+ publications: 100 scientists
101 publications 1,796+

This scientist: 391 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,796 publications or more.

Guido Germano D-index placement in Medicine in 2026

The chart shows the D-index (discipline H-index) distribution of Medicine scientists ranked by Research.com in 2026. The highlighted bar marks where Guido Germano sits on this spectrum.

70–71 D-Index: 226 scientists 72–73 D-Index: 391 scientists 74–75 D-Index: 574 scientists 76–77 D-Index: 730 scientists 78–79 D-Index: 891 scientists 80–81 D-Index: 972 scientists 82–83 D-Index: 1,027 scientists 84–85 D-Index: 1,003 scientists 86–87 D-Index: 960 scientists 88–89 D-Index: 970 scientists 90–91 D-Index: 922 scientists 92–93 D-Index: 839 scientists 94–95 D-Index: 808 scientists 96–97 D-Index: 779 scientists 98–99 D-Index: 668 scientists 100–101 D-Index: 611 scientists 102–103 D-Index: 630 scientists 104–105 D-Index: 513 scientists 106–107 D-Index: 541 scientists 108–109 D-Index: 445 scientists 110–111 D-Index: 429 scientists 112–113 D-Index: 400 scientists 114–115 D-Index: 393 scientists 116–117 D-Index: 318 scientists 118–119 D-Index: 302 scientists 120–121 D-Index: 287 scientists 122–123 D-Index: 255 scientists 124–125 D-Index: 256 scientists 126–127 D-Index: 252 scientists 128–129 D-Index: 230 scientists 130–131 D-Index: 179 scientists 132–133 D-Index: 168 scientists 134–135 D-Index: 163 scientists 136–137 D-Index: 159 scientists 138–139 D-Index: 134 scientists 140–141 D-Index: 134 scientists 142–143 D-Index: 118 scientists 144–145 D-Index: 109 scientists 146–147 D-Index: 106 scientists 148–149 D-Index: 74 scientists 150–151 D-Index: 79 scientists 152–153 D-Index: 80 scientists 154–155 D-Index: 87 scientists 156–157 D-Index: 57 scientists 158–159 D-Index: 74 scientists 160–161 D-Index: 69 scientists 162–163 D-Index: 60 scientists 164–165 D-Index: 53 scientists 166–167 D-Index: 39 scientists 168–169 D-Index: 42 scientists 170–171 D-Index: 32 scientists 172–173 D-Index: 39 scientists 174–175 D-Index: 40 scientists 176–177 D-Index: 28 scientists 178–179 D-Index: 19 scientists 180–181 D-Index: 23 scientists 182–183 D-Index: 31 scientists 184–185 D-Index: 18 scientists 186–187 D-Index: 20 scientists 188–189 D-Index: 22 scientists 190–191 D-Index: 13 scientists 192–193 D-Index: 21 scientists 194–195 D-Index: 12 scientists 196–197 D-Index: 12 scientists 198–199 D-Index: 14 scientists 200–201 D-Index: 15 scientists 202–203 D-Index: 13 scientists 204–205 D-Index: 10 scientists 206–207 D-Index: 8 scientists 208–209 D-Index: 4 scientists 210–211 D-Index: 12 scientists 212–213 D-Index: 11 scientists 214–215 D-Index: 10 scientists 216 D-Index: 4 scientists 217+ D-Index: 98 scientists
70 D-Index 217+

This scientist: 96 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 217 D-Index or more.

Overview

Guido Germano is affiliated with Cedars-Sinai Medical Center in the United States. Their research primarily focuses on the domain of Economics, Econometrics, and Finance, with specific expertise in subfields such as Management Science and Operations Research, Finance, Electrical and Electronic Engineering, Artificial Intelligence, and Economics and Econometrics.

The scientist's main research topics include:

  • Stock Market Forecasting Methods
  • Energy Load and Power Forecasting
  • Financial Markets and Investment Strategies
  • Forecasting Techniques and Applications
  • Sentiment Analysis and Opinion Mining
  • Topic Modeling
  • Stochastic processes and financial applications

Guido Germano has contributed scholarly articles to several publication venues, predominantly in the field of finance and quantitative analysis. Frequently cited journals and conference outlets include:

  • SSRN Electronic Journal
  • Finance research letters
  • Quantitative Finance
  • Methodology And Computing In Applied Probability
  • IMA Journal of Applied Mathematics

Notable recent papers authored or co-authored by Germano include:

  • "Sentiment trading with large language models," 2024, Finance research letters
  • "Sentiment Trading with Large Language Models," 2024, SSRN Electronic Journal
  • "Pricing methods for α-quantile and perpetual early exercise options based on Spitzer identities," 2020, Quantitative Finance
  • "Generative-Discriminative Machine Learning Models for High-Frequency Financial Regime Classification," 2025, Methodology And Computing In Applied Probability
  • "Large language models in finance: estimating financial sentiment for stock prediction," 2025, SSRN Electronic Journal

Collaborations have been a significant part of Germano's research activity, notably with several frequent co-authors. These include Kemal Kirtac, Carolyn E. Phelan, Daniele Marazzina, Andreas Koukorinis, and Gareth W. Peters.

The body of work reveals a strong focus on financial markets through quantitative and computational methods, including the application of machine learning and large language models for sentiment analysis and market prediction.

Best Publications

  • Optimal Medical Therapy With or Without Percutaneous Coronary Intervention to Reduce Ischemic Burden Results From the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial Nuclear Substudy

    Leslee J. Shaw;Daniel S. Berman;David J. Maron;G. B. John Mancini

  • Automatic quantification of ejection fraction from gated myocardial perfusion SPECT.

    G Germano;H Kiat;P B Kavanagh;M Moriel

  • Incremental Prognostic Value of Post-Stress Left Ventricular Ejection Fraction and Volume by Gated Myocardial Perfusion Single Photon Emission Computed Tomography

    Tali Sharir;Guido Germano;Paul B. Kavanagh;Shenhan Lai

  • Incremental value of prognostic testing in patients with known or suspected ischemic heart disease: a basis for optimal utilization of exercise technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography.

    Daniel S. Berman;Rory Hachamovitch;Hosen Kiat;Ishac Cohen

  • Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis.

    Manish Motwani;Damini Dey;Daniel S. Berman;Guido Germano

  • Separate acquisition rest thallium-201/stress technetium-99m sestamibi dual-isotope myocardial perfusion single-photon emission computed tomography : a clinical validation study

    Daniel S. Berman;Hosen Kiat;John D. Friedman;Fan Ping Wang

  • Impact of ischaemia and scar on the therapeutic benefit derived from myocardial revascularization vs. medical therapy among patients undergoing stress-rest myocardial perfusion scintigraphy.

    Rory Hachamovitch;Alan Rozanski;Leslee J. Shaw;Gregg W. Stone

  • Prediction of Myocardial Infarction Versus Cardiac Death by Gated Myocardial Perfusion SPECT: Risk Stratification by the Amount of Stress-Induced Ischemia and the Poststress Ejection Fraction

    Tali Sharir;Guido Germano;Xingping Kang;Howard C. Lewin

  • Determinants of risk and its temporal variation in patients with normal stress myocardial perfusion scans : What is the warranty period of a normal scan?

    Rory Hachamovitch;Sean Hayes;John D. Friedman;Ishac Cohen

  • Automatic Quantitation of Regional Myocardial Wall Motion and Thickening From Gated Technetium-99m Sestamibi Myocardial Perfusion Single-Photon Emission Computed Tomography

    Guido Germano;Jacob Erel;Jacob Erel;Howard Lewin;Howard Lewin;Paul B. Kavanagh

  • A New Algorithm for the Quantitation of Myocardial Perfusion SPECT. I: Technical Principles and Reproducibility

    G Germano;P B Kavanagh;P Waechter;J Areeda

  • Adenosine myocardial perfusion single-photon emission computed tomography in women compared with men: Impact of diabetes mellitus on incremental prognostic value and effect on patient management

    Daniel S Berman;Xingping Kang;Sean W Hayes;John D Friedman

  • Gated technetium-99m sestamibi for simultaneous assessment of stress myocardial perfusion, postexercise regional ventricular function and myocardial viability. Correlation with echocardiography and rest thallium-201 scintigraphy.

    Terrance Chua;Hosen Kiat;Guido Germano;Gerald Maurer

  • Underestimation of extent of ischemia by gated SPECT myocardial perfusion imaging in patients with left main coronary artery disease

    Daniel S Berman;Xingping Kang;Piotr J Slomka;James Gerlach

  • Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

    Daniel S. Berman;Aiden Abidov;Xingping Kang;Sean W. Hayes

  • Identification of severe and extensive coronary artery disease by automatic measurement of transient ischemic dilation of the left ventricle in dual-isotope myocardial perfusion SPECT

    Marco Mazzanti;Guido Germano;Hosen Kiat;Paul B. Kavanagh

  • Aortic Size Assessment by Noncontrast Cardiac Computed Tomography: Normal Limits by Age, Gender, and Body Surface Area

    Arik Wolak;Heidi Gransar;Louise E.J. Thomson;John D. Friedman

  • Prognostic Significance of Dyspnea in Patients Referred for Cardiac Stress Testing

    Aiden Abidov;Alan Rozanski;Rory Hachamovitch;Sean W. Hayes

  • Transient Ischemic Dilation Ratio of the Left Ventricle Is a Significant Predictor of Future Cardiac Events in Patients With Otherwise Normal Myocardial Perfusion SPECT

    Aiden Abidov;Jeroen J Bax;Sean W Hayes;Rory Hachamovitch

  • Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study

    Julian Betancur;Frederic Commandeur;Mahsaw Motlagh;Tali Sharir

Frequent Co-Authors

Daniel S. Berman
Daniel S. Berman Cedars-Sinai Medical Center
Piotr J. Slomka
Piotr J. Slomka Cedars-Sinai Medical Center
John D. Friedman
John D. Friedman Cedars-Sinai Medical Center
Sean W. Hayes
Sean W. Hayes Cedars-Sinai Medical Center
Damini Dey
Damini Dey Cedars-Sinai Medical Center
Leslee J. Shaw
Leslee J. Shaw Icahn School of Medicine at Mount Sinai
Sharmila Dorbala
Sharmila Dorbala Brigham and Women's Hospital
Philipp A. Kaufmann
Philipp A. Kaufmann University of Zurich
Marcelo F. Di Carli
Marcelo F. Di Carli Brigham and Women's Hospital
David E. Newby
David E. Newby University of Edinburgh

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