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Researcher · Technische Hochschule Ingolstadt · Germany

Jonathan Ganz

Jonathan Ganz publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine, on topics such as AI in cancer detection, Radiomics and Machine Learning in Medical Imaging and Digital Imaging for Blood Diseases.

ORCID 0009-0008-1299-8716 OpenAlex
World rank
#1,084,999
of 7,710,434 ranked researchers
Rank in Germany
#53,390
of 364,343
Works
741
Citations
348
Citations per work
0.5
h-index
9
i10-index 9Top 49% in Artificial Intelligence
Jonathan Ganz

What does Jonathan Ganz research?

Jonathan Ganz's work is mostly in Computer Science (37%), Medicine (20%), Biochemistry, Genetics and Molecular Biology (7%).

Physical Sciences: 276 works · 37.2% of their workComputer Science: 276 works · 37.2% of their workArtificial Intelligence: 179 works · 24.1% of their workComputer Vision and Pattern Recognition: 97 works · 13.1% of their workEverything else: 266 works · 35.9% of their workHealth Sciences: 148 works · 20.0% of their workMedicine: 148 works · 20.0% of their workPulmonary and Respiratory Medicine: 56 works · 7.6% of their workRadiology, Nuclear Medicine and Imaging: 51 works · 6.9% of their workHealth Informatics: 41 works · 5.5% of their workLife Sciences: 51 works · 6.9% of their workBiochemistry, Genetics and Molecular Biology: 51 works · 6.9% of their workMolecular Biology: 51 works · 6.9% of their workTHEIR WORKJonathan Ganz741works
Life Sciences7%Physical Sciences37%Health Sciences20%

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 Science27637.2%
  2. Everything else26635.9%
    1. Medicine14820.0%
    1. Biochemistry, Genetics and Molecular Biology516.9%
  1. 1Artificial Intelligence24% of their works
  2. 2Computer Vision and Pattern Recognition13% of their works
  3. 3Pulmonary and Respiratory Medicine8% of their works
  4. 4Radiology, Nuclear Medicine and Imaging7% of their works
  5. 5Molecular Biology7% of their works
  6. 6Health Informatics6% of their works

Research topics

Which keywords describe Jonathan Ganz's research?

The keywords of their largest research topics: Machine Learning, Convolutional Neural Networks, Medical Image Analysis, Deep Learning, Computer-Aided Detection, Histopathology Images, Feature Extraction and Medical Imaging.

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 24 words, with their numbers
  1. Machine Learning595 topics
  2. Convolutional Neural Networks332 topics
  3. Medical Image Analysis332 topics
  4. Deep Learning322 topics
  5. Computer-Aided Detection241 topic
  6. Histopathology Images241 topic
  7. Feature Extraction192 topics
  8. Medical Imaging182 topics
  9. Precision Medicine182 topics
  10. Image Processing172 topics
  11. Quantitative Analysis101 topic
  12. Radiomics101 topic
  13. Leukemia Classification91 topic
  14. Malaria Parasite Detection91 topic
  15. Artificial Intelligence81 topic
  16. Bioimage Analysis81 topic
  17. Canine Cancer81 topic
  18. Comparative Oncology81 topic
  19. Healthcare81 topic
  20. High-Content Screening81 topic
  21. Granular Cell Tumor61 topic
  22. Immunohistochemical Assessment61 topic
  23. Cancer Genomics51 topic
  24. Mutational Signatures51 topic

Where does Jonathan Ganz work?

Jonathan Ganz's main affiliation in the publication record is Technische Hochschule Ingolstadt, Germany.

How many publications and citations does Jonathan Ganz have?

OpenAlex counts 741 works and 348 citations for Jonathan Ganz, an h-index of 9, ranking #1,084,999 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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