Tezcan Ozrazgat‐Baslanti

MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery

2018 · 342 Zit. · Annals of Surgery

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

2016 · 196 Zit. · PLoS ONE

Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: A pilot usability study

2019 · 127 Zit. · Surgery

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform

2022 · 124 Zit. · JAMA Network Open

Artificial intelligence-enabled decision support in nephrology

2022 · 93 Zit. · Nature Reviews Nephrology

Uncertainty-aware deep learning in healthcare: A scoping review

2022 · 54 Zit. · PLOS Digital Health

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks

2023 · 45 Zit. · Scientific Reports

Machine Learning–Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review

2023 · 42 Zit. · JMIR Medical Informatics

Community-engaged artificial intelligence research: A scoping review

2024 · 16 Zit. · PLOS Digital Health

Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools

2024 · 14 Zit. · arXiv (Cornell University)

Electronic Health Record Data Quality and Performance Assessments: Scoping Review

2024 · 6 Zit. · JMIR Medical Informatics

Transparent AI: Developing an Explainable Interface for Predicting Postoperative Complications

2024 · 1 Zit. · arXiv (Cornell University)

Electronic Health Record Data Quality and Performance Assessments: A Scoping Review (Preprint)

2024 · 0 Zit.