Data Analytics: A Case Study In Healthcare

Mohammad Pourhomayoun, Cal State University, Los Angeles

Stevenson Hall 1300
12:00 PM - 12:50 PM

The increasing cost of chronic disease management demands novel technological solutions that shift healthcare services from clinical and hospital settings to a remote and homebound scenario. Alternative and innovative technologies such as Remote Health Monitoring Systems, Big Data Analytics, and Wireless Health Technologies allow for collecting physiological and contextual data from patients, and providing unique opportunities for real-time data analytics to predict health conditions and prevent medically adverse events. The development of effective predictive models and big data analytics systems, however, faces several fundamental challenges regarding their robustness, scalability, and real-time processing of big heterogeneous data. These challenges necessitate the design and development of robust and scalable data processing techniques based on advanced machine learning algorithms that can efficiently extract the information from physiological data and allow for knowledge discovery and analysis. This talk presents a research methodology for data analytics in next-generation remote health management platforms.