Brian W Locke, MD MSCI

Assistant Professor of Research, Department of Pulmonary and Critical Care Medicine, Intermountain Medical Center

I am a pulmonary and critical care physician-scientist focused on respiratory failure, diagnostic evidence, clinical prediction, and reproducible research informatics. My work connects respiratory measurement, Bayesian and statistical reasoning, and open clinical research workflows to practical questions in pulmonary and critical care medicine.

Brian W Locke, MD MSCI

About

I work in the Shock Trauma ICU and Schmidt Chest Clinic and serve as core faculty in the University of Utah Pulmonary and Critical Care Fellowship. I trained in computer science, medicine, medical education, and clinical investigation. My research centers on measurement, diagnostic evidence, prediction, and reproducible informatics for pulmonary and critical care medicine.

Current research and teaching interests include:

  • Respiratory measurement, hypercapnia, and follow-up after hospitalization
  • Diagnostic evidence, likelihood ratios, and clinical reasoning
  • Clinical prediction, EHR/NLP, and research informatics
  • Pulmonary vascular imaging and outcomes
  • Medical education around evidence-based reasoning

Research Approach

My academic work emphasizes methods that make clinical evidence more interpretable, reusable, and useful at the bedside:

  • Respiratory Measurement

    Using blood gas, bicarbonate, transcutaneous CO2, imaging, and EHR-derived signals to study acute and chronic respiratory failure.

  • Diagnostic Evidence

    Applying likelihood ratios, Bayesian reasoning, and information-theoretic framing to clinical reasoning and diagnostic uncertainty.

  • Clinical Prediction and Informatics

    Building EHR, NLP, and clinical AI workflows that support transparent prediction, phenotyping, and cohort construction.

  • Reproducible Statistical Workflows

    Developing open Stata, Python, and R pipelines for clinical research, including causal inference, prediction modeling, and clear visualization.

  • Medical Education

    Teaching evidence-based medicine, statistics, respiratory physiology, and diagnostic reasoning for trainees and clinicians.

Materials

Public code, teaching materials, reproducible analyses, and project artifacts are available in the materials index.

Browse GitHub-accessible materials