Gabriel Wardi

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm

2021 · 105 Zit. · Annals of Emergency Medicine

Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us

2023 · 33 Zit. · Critical Care Medicine

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence–Based Tools in Critical Care: Web-Based Survey Study

2022 · 23 Zit. · JMIR Perioperative Medicine

Predicting progression to septic shock in the emergency department using an externally generalizable machine learning algorithm

2020 · 10 Zit. · medRxiv

Learning health system strategies in the AI era

2025 · 9 Zit. · npj Health Systems

National Institutes of Health–Funded Artificial Intelligence and Machine Learning Research, 2019‐2023: Cross-Sectional Study

2026 · 2 Zit. · Journal of Medical Internet Research

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use

2025 · 1 Zit. · Clinical Infectious Diseases

Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey

2025 · 1 Zit. · Critical Care Explorations

Unreasonable effectiveness of training AI models locally

2025 · 0 Zit. · BMJ Quality & Safety

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence–Based Tools in Critical Care: Web-Based Survey Study (Preprint)

2022 · 0 Zit.

WITHDRAWN

2022 · 0 Zit. · CHEST Journal