Data Mining and Predictive Analytics – Clinical Applications

SFSU Campus, Thornton Hall 327, 1600 Holloway Ave (off 19th Avenue), San Francisco, USA

San Francisco State University
Center for Computing for Life Sciences (CCLS) Presents:
Data Mining and Predictive Analytics – Clinical Applications
6:00 PM June 8, 2011 SFSU

About the seminar/panel discussion
This is the second seminar of the new CCLS Bay Area Seminar Series. This seminar, in the format of a panel discussion, will provide insights and explore issues regarding the role of data mining and predictive analytics in life sciences with a focus on clinical applications. A subsequent panel will address this same topic with a focus on research applications. The panelists will describe the evolution of their experiences with data mining and predictive analytics and how they are using these processes today. This will include criteria considered to aggregate data from disparate sources into useable data sets and the interrogation of that data to formulate predictive tools. This seminar will be useful for practitioners, researchers, software developers, IT architects and information systems managers in life sciences.

Panelists
• Alex Bangs – Chief Information Officer, Crescendo Bioscience
• Ljubomir Buturovic – VP and Chief Scientist, Pathwork Diagnostics
• Steve Rosenberg – Chief Scientific Officer, CardioDx
• Jeanette Schmidt – VP Informatics, Affymetrix
• Moderator: Bob Dunkle – A.B.E.S Partners

Logistics
Date: Wednesday, June 8, 2011
Time: Networking: 6:00-7:00 PM, Seminar: 7:00-8:45 PM
Location: SFSU Campus, Thornton Hall 327, 1600 Holloway Ave (off 19th Avenue), San Francisco
SFSU directions and parking: http://www.sfsu.edu/~parking/ – we recommend parking structure 20, then follow the map http://www.sfsu.edu/~sfsumap/southeast.htm
Cost: No charge (light refreshments will be served)

Agenda
Welcome – Dragutin Petkovic, Director, CCLS
Overview of Seminar – Bob Dunkle
Experiences and perspective in data mining and predictive analytics – Panelists
How is data mining is tailored to a diverse set of needs?
How is data aggregated to include relevant data for mining applications?
Methods and processes to optimize predictive analytics performance
Use cases
Panel conversation and open Q&A

Sponsors:
CCLS – SFSU Center for Computing for Life Sciences http://cs.sfsu.edu/ccls/index.html
IBM Almaden Research Center http://www.almaden.ibm.com/

Attendance cost: No charge

Event organizer: SFSU Center for Computing for Life Sciences

Register for the Data Mining and Predictive Analytics – Clinical Applications