Area of research
Epidemiology · Artificial Intelligence
Research interest
Research interests include Sepsis Diagnosis and Treatment, Machine Learning in Healthcare, Cardiac Arrest and Resuscitation, and Artificial Intelligence in Healthcare and Education.
Development and prospective implementation of a large language model based system for early sepsis prediction
The Effect of Severe Sepsis and Septic Shock Management Bundle (SEP-1) Compliance and Implementation on Mortality Among Patients With Sepsis
Learning health system strategies in the AI era
Can we predict the future of respiratory failure prediction?
Impact of a deep learning sepsis prediction model on quality of care and survival
Large Language Models for More Efficient Reporting of Hospital Quality Measures
A Review of Bicarbonate Use in Common Clinical Scenarios
Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us
Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study
Inclusion of social determinants of health improves sepsis readmission prediction models
Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm
Artificial intelligence sepsis prediction algorithm learns to say “I don’t know”
Dispelling myths and misconceptions about the treatment of acute hyperkalemia
A Locally Optimized Data-Driven Tool to Predict Sepsis-Associated Vasopressor Use in the ICU
Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation
Age-related incidence and outcomes of sepsis in California, 2008–2015
Demystifying Lactate in the Emergency Department
Does Early and Appropriate Antibiotic Administration Improve Mortality in Emergency Department Patients with Severe Sepsis or Septic Shock?