Publications

See recent publications from our team.

Driving Tech
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Guiding Principle

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  • Hybrid electrode design and placement.

    High-frequency oscillations in intraoperative recordings from hybrid arrays with micro-and macrocontacts

    Journal of Neural Engineering

    Cecilia Schmitz, Katrina J Barth, Charles Wang, Zachary Spalding, Suseendrakumar Duraivel, Birgit Frauscher, Derek G Southwell, Gregory B Cogan, Justin Blanco and Jonathan Viventi

    Read more: High-frequency oscillations in intraoperative recordings from hybrid arrays with micro-and macrocontacts
  • Overview of the multi-agent system for automated BT-RADS classification.

    Agentic Automation of BT-RADS Scoring: End-to-End Multi-Agent System for Standardized Brain Tumor Follow-up Assessment

    arXiv

    Mohamed Sobhi Jabal, Jikai Zhang, Dominic LaBella, Jessica L. Houk, Dylan Zhang, Jeffrey D. Rudie, Kirti Magudia, Maciej A. Mazurowski, Evan Calabrese

    Read more: Agentic Automation of BT-RADS Scoring: End-to-End Multi-Agent System for Standardized Brain Tumor Follow-up Assessment
  • Publication cover

    116 Steroid Responsiveness Predicts the Feasibility of LITT in the Motor Cortex

    Neurosurgery

    Haskell-Mendoza, Aden P.; Jackson, Joshua MD; Flusche, Ann Marie; Reason, Elle; Gonzalez, Ariel T.; Srinivasan, Ethan; Lerner, Emily; Woo, Joshua; Herndon, James PhD; Calabrese, Evan; Fecci, Peter E. MD, PhD

    Read more: 116 Steroid Responsiveness Predicts the Feasibility of LITT in the Motor Cortex
  • Machine Learning Pipeline Overview

    Meningioma Who Grade Prediction Via a Novel Artificial Intelligence Algorithm Combining Preoperative MRI and Intraoperative Spectroscopy

    Journal of Neurological Surgery Part B: Skull Base

    Tanner J Zachem, Syed M Adil, Pranav I Warman, Jihad Abdelgadir, Christopher Tralie, Jordan Komisarow, Evan Calabrese, C. Rory Goodwin, Patrick J Codd

    Read more: Meningioma Who Grade Prediction Via a Novel Artificial Intelligence Algorithm Combining Preoperative MRI and Intraoperative Spectroscopy
  • Example Segmentation of Large T2 Lesion. Top Left: Axial, Top Right: 3D Reconstruction of Segmentation Region, Bottom Left: Coronal, Bottom Right: Sagittal.|

    Deep Learning Based Volumetric MRI Segmentation Algorithm for Vestibular Schwannoma Monitoring

    Journal of Neurological Surgery Part B: Skull Base

    Tanner J. Zachem, Syed M. Adil, Ethan Castellino, Luis Cruz Mondragon, Kristian Banovic, Ashley Lin, Jihad Abdelgadir, Patrick J. Codd, Ali Zomorodi, C. Rory Goodwin, Evan Calabrese

    Read more: Deep Learning Based Volumetric MRI Segmentation Algorithm for Vestibular Schwannoma Monitoring
  • Left: AUROC Cruve for Internal Validation (Gray) and Held-Out Test Set (Blue). Right: Calibration Curve.

    Artificial Intelligence Prediction of Meningioma Grade Using Preoperative MRI: A Large Multicenter Study

    Journal of Neurological Surgery Part B: Skull Base

    Syed M. Adil, Tanner J. Zachem, Pranav Warman, Jihad Abdelgadir, Nirav Patel, Benjamin D. Wissel, Kyle M. Walsh, Christopher J. Tralie, Andreas M. Rauschecker, Patrick J. Codd, Ali Zomorodi, Anoop Patel, Allan Friedman, Timothy W. Dunn, Evan Calabrese, C. Rory Goodwin

    Read more: Artificial Intelligence Prediction of Meningioma Grade Using Preoperative MRI: A Large Multicenter Study
  • Plot of interrater reliability for diabetes-specific Medication Regimen Complexity Index.

    Comparing the Effects of Diabetes-Specific and Overall Medication Regimen Complexity on Diabetes Distress

    The Science of Diabetes Self-Management and Care

    Kaye Min Teo, MD, Ryan J. Shaw, PhD, RN, Anastasia-Stefania Alexopoulos, MBBS, MHS, Gina Pennington Daniel Hatch, PhD, Qing Yang, PhD, Matthew J. Crowley, MD

    Read more: Comparing the Effects of Diabetes-Specific and Overall Medication Regimen Complexity on Diabetes Distress
  • RAFL overview

    RAFL: Generalizable Sim-to-Real of Soft Robots with Residual Acceleration Field Learning

    arXiv

    Dong Heon Cho, Boyuan Chen

    Read more: RAFL: Generalizable Sim-to-Real of Soft Robots with Residual Acceleration Field Learning
  • Performance of a LASSO-based model using EHR data to predict which children will meet criteria for recurrent AOM.

    Early life factors documented in electronic health records predict recurrent acute otitis media

    medRxiv

    Jillian H. Hurst, Congwen Zhao, Eileen M. Raynor, Janet Lee, Sarah A. Gitomer, Christopher W Woods, Matthew S. Kelly, Michael J. Smith, Benjamin A. Goldstein

    Read more: Early life factors documented in electronic health records predict recurrent acute otitis media
  • .Open multimedia modalKaplan–Meier plots for SWYC use (A), score (B), and time to first speech-language delay diagnosis.

    The Relationship Between the Survey of Well-being of Young Children and Speech-language Delay Diagnosis

    Journal of Developmental & Behavioral Pediatrics

    Danai Kasambira, Fannin, Jiang Shu, Geraldine Dawson, Gary Maslow, Benjamin A. Goldstein, Lauren Franz

    Read more: The Relationship Between the Survey of Well-being of Young Children and Speech-language Delay Diagnosis
  • GLP-1 RA versus Bupropion-Naltrexone

    Secondary Prevention of Cardiovascular Events in Patients with Overweight/Obesity in Routine Clinical Practice

    medRxiv

    Wenxin Guo, Maidou Wang, Jiwon Shin, Fan Li, Emily C. O’Brien, LáShauntá Glover, Kristina Bortfeld, Anqi Zhao, Ryan McDevitt, Cheryl Kalapura, Sarah Wu, Sahar Shibeika, Shannon Aymes, Michael Porter, Brian Mac Grory, Jay B. Lusk

    Read more: Secondary Prevention of Cardiovascular Events in Patients with Overweight/Obesity in Routine Clinical Practice
  • Lancet cover

    The need to develop health data transaction disclosure requirements to balance transparency, privacy, and progressive use

    The Lancet Digital Health

    Matthew G Crowson MD MBI, Jade Z H Tan, Jessilyn Dunn PhD, Jay Bhatt MD, Zachary Schneider, Daniel Forger PhD, Leo A Celi MD MPH, Matilda Dorotic PhD, Prof Bradley Malin

    Read more: The need to develop health data transaction disclosure requirements to balance transparency, privacy, and progressive use