# Corey Chivers

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/corey-chivers/

## Facts

| Field | Value |
| --- | --- |
| Citations | 2,923 |
| Field | Machine Learning in Healthcare |
| h-index | 22 |
| i10-index | 29 |
| Last Known Institution | University of Pennsylvania |
| OpenAlex ID | https://openalex.org/A5027620308 |
| ORCID iD | 0000-0001-7290-2183 |
| Works | 57 |

## Researcher papers

- [Economic Impacts of Non-Native Forest Insects in the Continental United States](https://scholariq.org/papers/economic-impacts-of-non-native-forest-insects-in-the-continental-united-states/)
- [Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic](https://scholariq.org/papers/locally-informed-simulation-to-predict-hospital-capacity-needs-during-the-covid/)
- [A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*](https://scholariq.org/papers/a-machine-learning-algorithm-to-predict-severe-sepsis-and-septic-shock/)
- [Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer](https://scholariq.org/papers/machine-learning-approaches-to-predict-6-month-mortality-among-patients-with/)
- [Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer](https://scholariq.org/papers/effect-of-integrating-machine-learning-mortality-estimates-with-behavioral/)
- [Clinician Perception of a Machine Learning–Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock*](https://scholariq.org/papers/clinician-perception-of-a-machine-learning-based-early-warning-system-designed/)
- [Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer](https://scholariq.org/papers/validation-of-a-machine-learning-algorithm-to-predict-180-day-mortality-for/)
- [A Reinforcement Learning Approach to Weaning of Mechanical Ventilation\n in Intensive Care Units](https://scholariq.org/papers/a-reinforcement-learning-approach-to-weaning-of-mechanical-ventilation-n-in/)
- [Rising complexity and falling explanatory power in ecology](https://scholariq.org/papers/rising-complexity-and-falling-explanatory-power-in-ecology/)
- [Long-term Effect of Machine Learning–Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer](https://scholariq.org/papers/long-term-effect-of-machine-learning-triggered-behavioral-nudges-on-serious/)

## Researcher topics

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Palliative Care and End-of-Life Issues](https://scholariq.org/topics/palliative-care-and-end-of-life-issues/)
- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Cancer survivorship and care](https://scholariq.org/topics/cancer-survivorship-and-care/)

## Researcher university

- [University of Pennsylvania](https://scholariq.org/institutions/university-of-pennsylvania/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.