Thursday, December 14
12:30pm
Room 403 (4th Floor)
Countway Library, HMS
Mauricio Santillana, Ph.D.
Assistant Professor
HMS and Boston Children’s Hospital
Machine Learning Approaches for Early Detection of Events in Healthcare. Epidemiological and Clinical Applications
I will describe machine learning methodologies that leverage Internet-based information from search engines, twitter microblogs, crowd-sourced disease surveillance systems, and electronic medical records, to successfully monitor and forecast disease outbreaks in multiple locations around the globe in near real-time. I will also present machine learning methodologies that leverage continuous-in-time information coming from bedside monitors in Intensive Care Units (ICU) to help improve patients’ health outcomes and reduce hospital costs. I will describe how these methodologies can be used to determine whether a patient in the ICU is ready to be extubated or not, or to estimate the length of stay upon a patient’s admission. If time allows, I will discuss some other machine learning methodologies capable of estimating, ahead of time, the volume of daily emergency visits to Boston Children’s Hospital or the likelihood that a patient may not show up to an appointment in an ambulatory clinic.
