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Researcher · Stanford University · United States

Nigam Haresh Shah

Nigam Haresh Shah publishes mostly in Artificial Intelligence, Molecular Biology and Health Information Management, on topics such as Biomedical Text Mining and Ontologies, Machine Learning in Healthcare and Artificial Intelligence in Healthcare and Education.

ORCID 0000-0001-9385-7158 OpenAlex
World rank
#22,669
of 7,710,434 ranked researchers
Rank in United States
#8,344
of 1,627,098
Works
563
Citations
36k
Citations per work
63.6
h-index
84
i10-index 303Top 0.1% in Artificial Intelligence
Nigam Haresh Shah

What does Nigam Haresh Shah research?

Nigam Haresh Shah's work is mostly in Computer Science (17%), Biochemistry, Genetics and Molecular Biology (16%), Medicine (9%).

Everything else: 266 works · 47.2% of their workPhysical Sciences: 118 works · 21.0% of their workComputer Science: 98 works · 17.4% of their workArtificial Intelligence: 98 works · 17.4% of their workMathematics: 20 works · 3.6% of their workStatistics and Probability: 20 works · 3.6% of their workHealth Sciences: 90 works · 15.9% of their workMedicine: 51 works · 9.1% of their workHealth Informatics: 32 works · 5.6% of their workInfectious Diseases: 20 works · 3.5% of their workHealth Professions: 38 works · 6.8% of their workHealth Information Management: 38 works · 6.8% of their workLife Sciences: 90 works · 15.9% of their workBiochemistry, Genetics and Molecular Biology: 90 works · 15.9% of their workMolecular Biology: 90 works · 15.9% of their workTHEIR WORKNigam Haresh Shah563works
Life Sciences16%Physical Sciences21%Health Sciences16%

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 else26647.2%
    1. Computer Science9817.4%
    2. Mathematics203.6%
    1. Medicine519.1%
    2. Health Professions386.8%
    1. Biochemistry, Genetics and Molecular Biology9015.9%
  1. 1Artificial Intelligence17% of their works
  2. 2Molecular Biology16% of their works
  3. 3Health Information Management7% of their works
  4. 4Health Informatics6% of their works
  5. 5Statistics and Probability4% of their works
  6. 6Infectious Diseases4% of their works

Research topics

Which keywords describe Nigam Haresh Shah's research?

The keywords of their largest research topics: Healthcare, Precision Medicine, Data Integration, Semantic Web, Electronic Health Records, Biomedical Ontologies, Text Mining and Deep Learning.

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. Healthcare2082 topics
  2. Precision Medicine2082 topics
  3. Data Integration1892 topics
  4. Semantic Web1892 topics
  5. Electronic Health Records1852 topics
  6. Biomedical Ontologies1361 topic
  7. Text Mining1361 topic
  8. Deep Learning1231 topic
  9. Predictive Modeling1231 topic
  10. Artificial Intelligence851 topic
  11. Machine Learning851 topic
  12. Clinical Decision Support Systems621 topic
  13. Health Information Exchange621 topic
  14. Linked Data531 topic
  15. Ontology531 topic
  16. Gene Set Enrichment Analysis491 topic
  17. Protein-Protein Interaction Networks491 topic
  18. Adverse Drug Reactions411 topic
  19. Pharmacovigilance411 topic
  20. Neural Networks391 topic
  21. Word Representation391 topic

Where does Nigam Haresh Shah work?

Nigam Haresh Shah's main affiliation in the publication record is Stanford University, United States.

How many publications and citations does Nigam Haresh Shah have?

OpenAlex counts 563 works and 35,827 citations for Nigam Haresh Shah, an h-index of 84, ranking #22,669 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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