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Researcher · PLA Information Engineering University · China

Jinjin Hai

Jinjin Hai publishes mostly in Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Biomedical Engineering, on topics such as Radiomics and Machine Learning in Medical Imaging, Medical Imaging and Analysis and AI in cancer detection.

ORCID 0000-0002-3767-8152 OpenAlex
World rank
#2,509,774
of 7,710,434 ranked researchers
Rank in China
#392,414
of 978,568
Works
39
Citations
836
Citations per work
21.4
h-index
11
i10-index 11Top 50% in Radiology, Nuclear Medicine and Imaging
Jinjin Hai

What does Jinjin Hai research?

Jinjin Hai's work is mostly in Medicine (31%), Computer Science (26%), Engineering (15%).

Physical Sciences: 16 works · 41.1% of their workComputer Science: 10 works · 25.9% of their workArtificial Intelligence: 6 works · 15.2% of their workComputer Vision and Pattern Recognition: 4 works · 10.7% of their workEngineering: 6 works · 15.2% of their workBiomedical Engineering: 6 works · 15.2% of their workHealth Sciences: 12 works · 31.2% of their workMedicine: 12 works · 31.2% of their workRadiology, Nuclear Medicine and Imaging: 8 works · 19.6% of their workPulmonary and Respiratory Medicine: 3 works · 7.1% of their workPathology and Forensic Medicine: 2 works · 4.5% of their workEverything else: 11 works · 27.7% of their workTHEIR WORKJinjin Hai39works
Physical Sciences41%Health Sciences31%

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 Science1025.9%
    2. Engineering615.2%
    1. Medicine1231.2%
  3. Everything else1127.7%
  1. 1Radiology, Nuclear Medicine and Imaging20% of their works
  2. 2Artificial Intelligence15% of their works
  3. 3Biomedical Engineering15% of their works
  4. 4Computer Vision and Pattern Recognition11% of their works
  5. 5Pulmonary and Respiratory Medicine7% of their works
  6. 6Pathology and Forensic Medicine4% of their works

Research topics

Which keywords describe Jinjin Hai's research?

The keywords of their largest research topics: Deep Learning, Medical Image Analysis, Machine Learning, Texture Analysis, Medical Imaging, Radiomics, Convolutional Neural Networks and Spine Segmentation.

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. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 21 words, with their numbers
  1. Deep Learning324 topics
  2. Medical Image Analysis283 topics
  3. Machine Learning262 topics
  4. Texture Analysis222 topics
  5. Medical Imaging161 topic
  6. Radiomics161 topic
  7. Convolutional Neural Networks142 topics
  8. Spine Segmentation121 topic
  9. Vertebrae Detection121 topic
  10. Computer-Aided Detection101 topic
  11. Histopathology Images101 topic
  12. Graph Cuts61 topic
  13. Image Segmentation61 topic
  14. Intervertebral Disc51 topic
  15. Lumbar Disc Degeneration51 topic
  16. Dual-Energy CT41 topic
  17. Image Recognition41 topic
  18. Material Differentiation41 topic
  19. Metastatic41 topic
  20. Object Detection41 topic
  21. Renal Cell Carcinoma41 topic

Where does Jinjin Hai work?

Jinjin Hai's main affiliation in the publication record is PLA Information Engineering University, China.

How many publications and citations does Jinjin Hai have?

OpenAlex counts 39 works and 836 citations for Jinjin Hai, an h-index of 11, ranking #2,509,774 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation 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.

Discussion

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