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Corey Chivers

ResearcherPublications, citations & collaboration network

Corey Chivers is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 57 works, 2,923 citations, an h-index of 22 and an i10-index of 29.

57
Works
2,923
Citations
22
h-index
29
i10-index

How has Corey Chivers's publication output changed over time?

ScholarIQpublication output · 2011–2023

Output grew0% over the shown period — from 1 works in 2011 to 1 in 2023.

1
1
1
3
3
1
201120142017201920202023

What are the most-cited papers on Corey Chivers?

ScholarIQmost cited works
Economic Impacts of Non-Native Forest Insects in the Continental United States
Juliann E. Aukema, Brian Leung, Kent Kovacs, Corey Chivers, Kerry O. Britton, Jeffrey Englin, Susan J. Frankel, Robert G. Haight, Thomas P. Holmes, Andrew M. Liebhold, Deborah G. McCullough, Betsy Von Holle
PLoS ONE. 2011616 CitationsOPEN ACCESS
Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic
Gary E. Weissman, Andrew Crane‐Droesch, Corey Chivers, ThaiBinh Luong, Asaf Hanish, Michael Z. Levy, Jason Lubken, Michael Becker, Michael Draugelis, George L. Anesi, Patrick J. Brennan, Jason D. Christie, C. William Hanson, Mark E. Mikkelsen, Scott D. Halpern
Annals of Internal Medicine. 2020320 Citations
A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*
H.M. Giannini, Jennifer C. Ginestra, Corey Chivers, Michael Draugelis, Asaf Hanish, William D. Schweickert, Barry D. Fuchs, L. Meadows, Michael J. Lynch, Patrick J. Donnelly, Kimberly Pavan, Neil O. Fishman, C. William Hanson, Craig A. Umscheid
Critical Care Medicine. 2019268 CitationsOPEN ACCESS
Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
Ravi B. Parikh, Christopher R. Manz, Corey Chivers, Susan Harkness Regli, Jennifer Braun, Michael Draugelis, Lynn M. Schuchter, Lawrence N. Shulman, Amol S. Navathe, Mitesh S. Patel, Nina O’Connor
JAMA Network Open. 2019247 CitationsOPEN ACCESS
Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer
Christopher R. Manz, Ravi B. Parikh, Dylan S. Small, Chalanda N. Evans, Corey Chivers, Susan Harkness Regli, C. William Hanson, Justin E. Bekelman, Charles Rareshide, Nina O’Connor, Lynn M. Schuchter, Lawrence N. Shulman, Mitesh S. Patel
JAMA Oncology. 2020178 CitationsOPEN ACCESS

Related on ScholarIQ

University of Pennsylvania
Institution
Economic Impacts of Non-Native Forest Insects in the Continental United States
Paper
Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic
Paper
A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*
Paper
Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
Paper
Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer
Paper
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