Phoebe Miller

University of California, San Francisco

Papers

1

Total Citations

7

H-Index

1

About

Phoebe Miller is a rising leader in surgical outcomes research, with a focus on leveraging machine learning to refine perioperative risk assessment. Her most impactful work introduces a novel machine learning approach to predict textbook outcomes in colectomy—a composite measure of an ideal postoperative recovery, free from complications, readmission, or mortality. While traditional risk calculators often emphasize adverse events, Miller’s research shifts the paradigm toward predicting success, offering a more nuanced tool for clinical decision-making, particularly for high-risk patients. This study, published in 2023, has already garnered 7 citations, signaling its early influence in the field. By integrating advanced analytics with patient-centered endpoints, Miller is helping to transform how surgeons evaluate and communicate procedural risk. Her work bridges the gap between data science and clinical practice, providing actionable insights that can improve shared decision-making and surgical quality. As a researcher, Miller exemplifies the next generation of surgical scientists—combining technical rigor with a deep commitment to improving patient outcomes through precision medicine.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy
7 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of California, San Francisco

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago