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Researcher · Dascena (United States) · United States

Abigail Green‐Saxena

Abigail Green‐Saxena publishes mostly in Epidemiology, Artificial Intelligence and Molecular Biology, on topics such as Sepsis Diagnosis and Treatment, Machine Learning in Healthcare and COVID-19 diagnosis using AI.

ORCID 0000-0002-8502-6589 OpenAlex
World rank
#371,515
of 7,710,434 ranked researchers
Rank in United States
#132,544
of 1,627,098
Works
45
Citations
1.4k
Citations per work
30.7
h-index
20
i10-index 24Top 23% in Epidemiology
Abigail Green‐Saxena

What does Abigail Green‐Saxena research?

Abigail Green‐Saxena's work is mostly in Medicine (30%), Computer Science (10%), Biochemistry, Genetics and Molecular Biology (8%).

Everything else: 22 works · 48.4% of their workHealth Sciences: 13 works · 29.6% of their workMedicine: 13 works · 29.6% of their workEpidemiology: 8 works · 16.9% of their workInfectious Diseases: 3 works · 7.6% of their workRadiology, Nuclear Medicine and Imaging: 2 works · 5.1% of their workPhysical Sciences: 6 works · 14.4% of their workComputer Science: 5 works · 10.2% of their workArtificial Intelligence: 5 works · 10.2% of their workEnvironmental Science: 2 works · 4.2% of their workEcology: 2 works · 4.2% of their workLife Sciences: 3 works · 7.6% of their workBiochemistry, Genetics and Molecular Biology: 3 works · 7.6% of their workMolecular Biology: 3 works · 7.6% of their workTHEIR WORKAbigailGreen‐Saxena45works
Life Sciences8%Physical Sciences14%Health Sciences30%

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. Everything else2248.4%
    1. Medicine1329.6%
    1. Computer Science510.2%
    2. Environmental Science24.2%
    1. Biochemistry, Genetics and Molecular Biology37.6%
  1. 1Epidemiology17% of their works
  2. 2Artificial Intelligence10% of their works
  3. 3Molecular Biology8% of their works
  4. 4Infectious Diseases8% of their works
  5. 5Radiology, Nuclear Medicine and Imaging5% of their works
  6. 6Ecology4% of their works

Research topics

Which keywords describe Abigail Green‐Saxena's research?

The keywords of their largest research topics: Biomarkers, Sepsis, Deep Learning, Healthcare, Management, Septic Shock, Electronic Health Records and Predictive Modeling.

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 20 words, with their numbers
  1. Biomarkers182 topics
  2. Sepsis182 topics
  3. Deep Learning172 topics
  4. Healthcare152 topics
  5. Management141 topic
  6. Septic Shock141 topic
  7. Electronic Health Records111 topic
  8. Predictive Modeling111 topic
  9. COVID-1961 topic
  10. Medical Imaging61 topic
  11. Anaerobic51 topic
  12. Methane Oxidation51 topic
  13. Acute Kidney Injury41 topic
  14. Big Data Analytics41 topic
  15. Clinical Characteristics41 topic
  16. Machine Learning41 topic
  17. Marine Microbes41 topic
  18. Microbial Biogeography41 topic
  19. Renal Failure41 topic
  20. SARS-CoV-241 topic

Where does Abigail Green‐Saxena work?

Abigail Green‐Saxena's main affiliation in the publication record is Dascena (United States), United States.

How many publications and citations does Abigail Green‐Saxena have?

OpenAlex counts 45 works and 1,381 citations for Abigail Green‐Saxena, an h-index of 20, ranking #371,515 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.

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