Applications of Real-Time Streaming Computing and Machine Learning in Intensive Care Units: Dr. Sharath Cholleti, Emory

  • Starts: 11:00 am on Wednesday, July 24, 2013
  • Ends: 12:00 pm on Wednesday, July 24, 2013
Description: Patients in intensive care units (ICU) are continuously monitored for their critical illness or post-surgery complications. Variety of sensors measure patients’ physiology and generate high velocity and high volume streaming data. Part of the raw data and some calculated metrics are displayed on computer monitors for the clinicians to observe current state of the patients. Progress in critical care monitoring has been slow due to technical, clinical, financial, and regulatory reasons. Meanwhile tremendous progress has been in made in the fields of machine learning, stream computing, and data visualization in the past decade along with middleware to interface with proprietary ICU monitoring systems and electronic health record systems in real time. In this talk, I will discuss how above technologies are being applied to create the next generation ICU monitoring with numerous algorithms to keep track of large number of patients 24/7 to detect and predict adverse trends and events while improving patient care and reducing costs. Bio: Dr. Sharath Cholleti is a Senior Research Scientist at the Center for Comprehensive Informatics at Emory University. He received his Ph.D. and M.S. in Computer Science from Washington University in St. Louis, and B.Tech. in Computer Science and Engineering from Indian Institute of Technology, Guwahati, India. His research interests are in machine learning, data mining, and their applications to medicine. He developed machine learning algorithms and applications for variety of medical software involving pathology images, radiology images, glycomics data, and clinical data from electronic health records and intensive care units. His current work involves development of predictive modeling software for 30-day hospital readmission, and development of real-time analytics and visualization system for intensive care units
Location:
MCS 148