Todd Hollon

Associate Professor
University of Michigan
tocho (at) umich.edu


Patient forecasting

Machine learning has the potential to revolutionize the way we predict patient outcomes. Electronic medical records (EMR) have streamlined data collection and made it easier than ever to use ML algorithms to assist in patient care. Our work has focused on predicting (1) how well patients will recover after surgery and (2) what will ultimately affect their long-term outcome and survival. We use ML algorithms that allow for transparency and interpretability, both of which are essential to trust the recommendations of ML decision-support tools in healthcare. By identifying the specific set of symptoms, radiographic findings, laboratory values, etc. that our models use for prediction, physicians can use ML recommendations in the appropriate clinical context for personalized treatment decisions.

  1. Figure from: A machine learning approach to predict early outcomes after pituitary adenoma surgery
    Todd C Hollon, Adish Parikh, Balaji Pandian, Jamaal Tarpeh, Daniel A Orringer, Ariel L Barkan, Erin L McKean, Stephen E Sullivan
    JOURNAL OF NEUROSURGERY · 2018

    This study develops a machine learning model to forecast early postoperative outcomes after pituitary adenoma surgery, supporting risk stratification and perioperative planning.


  2. Figure from: Clinical Factors Associated With ICU-Specific Care Following Supratentoral Brain Tumor Resection and Validation of a Risk Prediction Score
    Lynze R Franko, Todd Hollon, Joseph Linzey, Christopher Roark, Venkatakrishna Rajajee, Kyle Sheehan, Magnus Teig, Shawn Hervey-Jumper, Jason Heth, Daniel Orringer, Craig A Williamson
    CRITICAL CARE MEDICINE · 2018

    This work identifies predictors of ICU-level needs after supratentorial brain tumor resection and validates a risk score to guide postoperative triage and resource allocation.


  3. Figure from: Surgical Treatment of Olfactory Neuroblastoma: Major Complication Rates, Progression Free and Overall Survival
    Aileen Wertz, Todd Hollon, Lawrence J Marentette, Stephen E Sullivan, Jonathan B McHugh, Erin L McKean
    JOURNAL OF NEUROLOGICAL SURGERY · 2018

    This outcomes study reports complication profiles and survival metrics after surgical treatment of olfactory neuroblastoma.


  4. Figure from: Ventriculoscopic Surgery for Cystic Retrochiasmatic Craniopharyngiomas: Indications, Surgical Technique, and Short-Term Patient Outcomes
    Todd C Hollon, Luis E Savastano, David Altshuler, Ariel L Barkan, Stephen E Sullivan
    OPERATIVE NEUROSURGERY · 2017

    This paper outlines indications and technique for ventriculoscopic treatment of cystic retrochiasmatic craniopharyngiomas and reports short-term clinical outcomes in treated patients.


  5. Figure from: Supratentorial hemispheric ependymomas: an analysis of 109 adults for survival and prognostic factors
    Todd Hollon, Vincent Nguyen, Brandon W Smith, Spencer Lewis, Larry Junck, Daniel A Orringer
    JOURNAL OF NEUROSURGERY · 2016

    This cohort study of 109 adults with supratentorial hemispheric ependymoma characterizes survival outcomes and prognostic factors to inform treatment planning and follow-up.


  6. Figure from: Outcome of Transsphenoidal Surgery for Cushing Disease: A Single-Center Experience Over 32 Years
    William F Chandler, Ariel L Barkan, Todd Hollon, Alla Sakharova, Jayson Sack, Barunashish Brahma, David E Schteingart
    NEUROSURGERY · 2016

    This long-term single-center analysis reports outcomes of transsphenoidal surgery for Cushing disease, identifying patterns in remission and recurrence over three decades of care.


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