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Researcher · Rochester Institute of Technology · United States

Maryam Toloubidokhti

Maryam Toloubidokhti publishes mostly in Cardiology and Cardiovascular Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, on topics such as Cardiac electrophysiology and arrhythmias, ECG Monitoring and Analysis and Cardiac Arrhythmias and Treatments.

ORCID 0000-0003-2923-441X OpenAlex
World rank
#5,785,403
of 7,710,434 ranked researchers
Rank in United States
#1,430,710
of 1,627,098
Works
21
Citations
72
Citations per work
3.4
h-index
5
i10-index 3Top 84% in Cardiology and Cardiovascular Medicine
Maryam Toloubidokhti

What does Maryam Toloubidokhti research?

Maryam Toloubidokhti's work is mostly in Medicine (52%), Computer Science (21%), Engineering (5%).

Health Sciences: 11 works · 51.7% of their workMedicine: 11 works · 51.7% of their workCardiology and Cardiovascular Medicine: 9 works · 44.8% of their workRadiology, Nuclear Medicine and Imaging: 1 works · 6.9% of their workPhysical Sciences: 7 works · 31.0% of their workComputer Science: 4 works · 20.6% of their workArtificial Intelligence: 4 works · 17.2% of their workComputer Vision and Pattern Recognition: 1 works · 3.4% of their workEngineering: 1 works · 5.2% of their workElectrical and Electronic Engineering: 1 works · 5.2% of their workPhysics and Astronomy: 1 works · 5.2% of their workStatistical and Nonlinear Physics: 1 works · 5.2% of their workEverything else: 4 works · 17.3% of their workTHEIR WORKMaryamToloubidokhti21works
Physical Sciences31%Health Sciences52%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Medicine1151.7%
    1. Computer Science420.6%
    2. Engineering15.2%
    3. Physics and Astronomy15.2%
  3. Everything else417.3%
  1. 1Cardiology and Cardiovascular Medicine45% of their works
  2. 2Artificial Intelligence17% of their works
  3. 3Radiology, Nuclear Medicine and Imaging7% of their works
  4. 4Statistical and Nonlinear Physics5% of their works
  5. 5Electrical and Electronic Engineering5% of their works
  6. 6Computer Vision and Pattern Recognition3% of their works

Research topics

Which keywords describe Maryam Toloubidokhti's research?

The keywords of their largest research topics: Deep Learning, Arrhythmias, Long-QT Syndrome, Sudden Cardiac Death, Arrhythmia Detection, ECG Signal, Machine Learning and Catheter Ablation.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 19 words, with their numbers
  1. Deep Learning185 topics
  2. Arrhythmias162 topics
  3. Long-QT Syndrome121 topic
  4. Sudden Cardiac Death121 topic
  5. Arrhythmia Detection71 topic
  6. ECG Signal71 topic
  7. Machine Learning52 topics
  8. Catheter Ablation41 topic
  9. Ventricular Tachycardia41 topic
  10. Electronic Health Records31 topic
  11. Healthcare31 topic
  12. Interpretable Models31 topic
  13. Machine Learning Interpretability31 topic
  14. Magnetic Resonance Imaging31 topic
  15. Model Reduction31 topic
  16. Partial Differential Equations31 topic
  17. Perfusion Imaging31 topic
  18. Gaussian Processes21 topic
  19. Variational Inference21 topic

Where does Maryam Toloubidokhti work?

Maryam Toloubidokhti's main affiliation in the publication record is Rochester Institute of Technology, United States.

How many publications and citations does Maryam Toloubidokhti have?

OpenAlex counts 21 works and 72 citations for Maryam Toloubidokhti, an h-index of 5, ranking #5,785,403 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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