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Researcher · Stanford University · United States

Henrik Marklund

Henrik Marklund publishes mostly in Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, on topics such as Domain Adaptation and Few-Shot Learning, COVID-19 diagnosis using AI and Machine Learning and Data Classification.

ORCID 0009-0004-5033-6175 OpenAlex
World rank
#2,242,499
of 7,710,434 ranked researchers
Rank in United States
#671,207
of 1,627,098
Works
19
Citations
3.6k
Citations per work
187.3
h-index
9
i10-index 9Top 49% in Artificial Intelligence
Henrik Marklund

What does Henrik Marklund research?

Henrik Marklund's work is mostly in Computer Science (46%), Medicine (22%), Neuroscience (4%).

Physical Sciences: 9 works · 45.6% of their workComputer Science: 9 works · 45.6% of their workArtificial Intelligence: 7 works · 37.0% of their workComputer Science Applications: 1 works · 4.3% of their workComputer Vision and Pattern Recognition: 1 works · 4.3% of their workEverything else: 5 works · 28.4% of their workHealth Sciences: 4 works · 21.7% of their workMedicine: 4 works · 21.7% of their workRadiology, Nuclear Medicine and Imaging: 2 works · 13.0% of their workPulmonary and Respiratory Medicine: 2 works · 8.7% of their workLife Sciences: 1 works · 4.3% of their workNeuroscience: 1 works · 4.3% of their workCognitive Neuroscience: 1 works · 4.3% of their workTHEIR WORKHenrik Marklund19works
Life Sciences4%Physical Sciences46%Health Sciences22%

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. Computer Science945.6%
  2. Everything else528.4%
    1. Medicine421.7%
    1. Neuroscience14.3%
  1. 1Artificial Intelligence37% of their works
  2. 2Radiology, Nuclear Medicine and Imaging13% of their works
  3. 3Pulmonary and Respiratory Medicine9% of their works
  4. 4Computer Vision and Pattern Recognition4% of their works
  5. 5Computer Science Applications4% of their works
  6. 6Cognitive Neuroscience4% of their works

Research topics

Which keywords describe Henrik Marklund's research?

The keywords of their largest research topics: Transfer Learning, Convolutional Neural Networks, Deep Learning, Meta-Learning, Artificial Intelligence, Machine Learning, Medical Imaging and Domain Adaptation.

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 23 words, with their numbers
  1. Transfer Learning112 topics
  2. Convolutional Neural Networks103 topics
  3. Deep Learning103 topics
  4. Meta-Learning102 topics
  5. Artificial Intelligence72 topics
  6. Machine Learning73 topics
  7. Medical Imaging72 topics
  8. Domain Adaptation61 topic
  9. Few-Shot Learning61 topic
  10. COVID-1951 topic
  11. Chest X-Ray51 topic
  12. Hyperparameter Optimization41 topic
  13. Noisy Labels41 topic
  14. Histopathology Images31 topic
  15. Medical Image Analysis31 topic
  16. Clinical Decision Support21 topic
  17. Colorectal Cancer21 topic
  18. Educational Data Mining21 topic
  19. Healthcare21 topic
  20. Image Recognition21 topic
  21. Learning Analytics21 topic
  22. Object Detection21 topic
  23. Screening21 topic

Where does Henrik Marklund work?

Henrik Marklund's main affiliation in the publication record is Stanford University, United States.

How many publications and citations does Henrik Marklund have?

OpenAlex counts 19 works and 3,559 citations for Henrik Marklund, an h-index of 9, ranking #2,242,499 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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