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Achievement: StarstruckAchievement: Pull SharkAchievement: Arctic Code Vault Contributor
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instigatorofawe/README.md

I'm Ran Liu. I completed my PhD in Biomedical Engineering at the Johns Hopkins University in 2021.

I am currently a Postdoctoral Scholar with Dr. Patrick Purdon at Stanford University in the department of Anesthesiology, Perioperative, and Pain Medicine. Our lab was formerly at Massachusetts General Hospital and Harvard Medical School in the department of Anesthesiology, Critical Care, and Pain Medicine. My dissertation was on the application of statistical and machine learning methods for decision support in critical care. Currently, I'm working on research in computational neuroscience and anesthsiology, on treatment optimization in anesthesia and pain management, and on the characterization of consciousness and disease states.

I am broadly interested in the application of dynamical systems modeling, machine learning, and artificial intelligence methods to problems in medicine. In particular, I am interested in brain function, consciousness, and cognition, and in the intersection of machine learning and model-based methods.

https://scholar.google.com/citations?user=bshgBtkAAAAJ

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  1. shockalert-documented shockalert-documented Public

    Data-driven discovery of a novel sepsis pre-shock state predicts impending septic shock in the ICU

    HTML 15 8

  2. clustering_manuscript clustering_manuscript Public

    Code associated with the paper, "Spectral Clustering of Risk Score Trajectories Stratifies Sepsis Patients by Clinical Outcome and Interventions Received"

    R 2 1

  3. cardiac.output.R cardiac.output.R Public

    ABP Waveform Utilities and Cardiac Output Estimators

    R 2 1

  4. pain_prediction_pops pain_prediction_pops Public

    This is the official code repository for the manuscript "Development and prospective validation of postoperatve pain prediction from preoperative EHR data using ICD-10 and CPT attention-based set e…

    R 2

  5. balance_assessment balance_assessment Public

    Utilities for assessing covariate balance for causal inference

    R