College of Medicine
Loftus Lab
Led by Tyler J Loftus · Surgery
What we study
The Loftus Lab studies how machine learning can improve patient care after surgery, focusing on data science and personalized decision-making. Their research uses computational methods to analyze patient data.
What working here is like
- Computational
- Clinical
- Coding required
- Project
- 1
- Papers
- 5
Current projects
Graduate Performance Profiles to Enhance Learning Analytics and Precision Program Improvement in Vascular Surgery
Uses data analytics to improve training and outcomes in vascular surgery.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- Development and External Validation of a Machine Learning–Based Simplified Injury Severity Score for Improved Trauma Mortality Prediction
2026 · Journal of the American College of Surgeons
Builds a machine learning model to predict trauma patient mortality using early clinical data.
- Association Between Metabolic and Bariatric Surgery and Melanoma Risk: A Systematic Review and Meta-analysis of Observational Studies
2026 · Obesity Surgery
Looks at whether metabolic and bariatric surgery affects melanoma risk in a large group of patients.
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- Integrating Artificial Intelligence Competencies Across the Six ACGME Core Competencies: A Proposed Framework for Graduate Medical Education
2026 · Advances in Medical Education and Practice
Proposes adding AI skills to medical training standards.
- Matching Surgical Datasets to Prediction Tasks: NSQIP and Non-NSQIP Artificial Intelligence Models Across Specialties
2026 · Journal of the American College of Surgeons
Compares AI models trained on hospital data with those using other data.
- Standard setting in the era of workplace-based assessment: a pilot exploration
2026 · Global Surgical Education - Journal of the Association for Surgical Education
Tests whether existing methods can set performance standards for workplace skills.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
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