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Jane Paik Kim
Stanford University
$1,833,811
Attributed
$1,833,811
Total exposure
1
Grants
1
Lead (contact PI)
Attributed= this PI's even-split share of every grant they're on (the fair, additive number). Exposure = full size of all those grants. They are the sole PI on all grants (the two match).
Funding over time
peak $600.3K · FY2020–23$1M$750K$500K$250K$0
'20
'21
'22
'23
Funding mix
By agency
NIH$1,833,811 · 1
By mechanism
R01$1,833,811 · 1
Top collaborators
No co-investigators on record.
Most similar at Stanford University
Same institution · by research overlap
- Holly K Tabor$5,270,163
- Karl Alexander Deisseroth$77,564,196
- Sean Albert Quirin$3,173,202
- Meghan Halley$1,539,490
- Lauren Elisabeth Harrison$915,775
Others in their field
Other Emerging Leaders on “Medicine”
- Sonia M Thomas · Research Triangle Institute$700,865,642
- Tracy L Nolen · Research Triangle Institute$474,487,152
- Leonard Freedman · Leidos Biomedical Research, Inc.$324,392,296
- Lynn Briscoe · Leidos Biomedical Research, Inc.$111,781,421
- Leonard Freedmand · Leidos Biomedical Research, Inc.$52,916,621
- Susan M Landau · University Of California Berkeley$47,252,026
Research focus
MedicineResearch PersonnelFundingMachine LearningPersonsPrecision MedicineEvidence BaseFailureFutureLearningMethodologyAffectAlgorithmsPopulation HealthEthical IssuesEthicsDecision MakingFaceArtificial IntelligenceDimensionsInnovationInterviewAttentionResponse
Grant awards (5)
Stakeholder Guidance to Anticipate and Address Ethical Challenges in Applications of Machine Learning and Artificial Intelligence in Algorithmic Medicine: a Novel Empirical Approach$401,288
R01 · FY2023 · TR · contact PI
Stakeholder Guidance to Anticipate and Address Ethical Challenges in Applications of Machine Learning and Artificial Intelligence in Algorithmic Medicine: a Novel Empirical Approach$402,865
R01 · FY2022 · TR · contact PI
Stakeholder Guidance to Anticipate and Address Ethical Challenges in Applications of Machine Learning and Artificial Intelligence in Algorithmic Medicine: a Novel Empirical Approach$442,905
R01 · FY2021 · TR · contact PI
Stakeholder Guidance to Anticipate and Address Ethical Challenges in Applications of Machine Learning and Artificial Intelligence in Algorithmic Medicine: a Novel Empirical Approach$157,426
R01 · FY2021 · TR · contact PI
Stakeholder Guidance to Anticipate and Address Ethical Challenges in Applications of Machine Learning and Artificial Intelligence in Algorithmic Medicine: a Novel Empirical Approach$429,327
R01 · FY2020 · TR · contact PI