Northwest Healthcare Analytics Workshop

The Center For Data Science, University of Washington Tacoma and the Seattle chapter of ACM SIGKDD welcomes you to participate in the first Northwestern regional healthcare analytics workshop.

The objectives of this workshop is to present problems of growing relevance in healthcare and discuss how advanced machine learning techniques can be used to address them through interactions between clinicians and ML-researchers. The workshop will offer the opportunity for healthcare analytics novices, experts and managers to engage in meaningful conversation and learning from relevant incident handling topics and ideas.

Important Dates

Speaker proposal deadline: TBA
Review Submission: TBA
Acceptance Notification: TBA
Workshop: TBA

We invite speakers for the Northwest Healthcare Analytics (NWHA) workshop. If you have relevant expertise to share as a speaker or moderator, we invite you to apply. Session proposals should focus on the role analytics can play in helping provider and payer organizations transition from volume-based to value-based healthcare. Specifically, we want presentations that clearly demonstrate how healthcare payers and providers are using data and analytics to improve and standardize clinical care, reduce costs, achieve population health, and make better strategic decisions for their organizations. We are accepting submissions in all areas of healthcare analytics, employee benefits and healthcare including:

Topics focused on Analytics, ML and Data Mining

  • Importance of analytics in healthcare
  • Statistical analysis and characterization of healthcare data
  • Visual analytics in Healthcare
  • Personalized health
  • Personalized medicine and genomics
  • Secure machine learning for healthcare data
  • Privacy and Security: Information Sharing
  • Care pathway recommendation system
  • Patient centered information retrieval
  • Healthcare sensor data mining and analytics
  • Information systems including electronic health records, hospital information systems, data exchange and integration

Topics Focused on Care Providers, Managers, and Payers

  • Corporate Wellness: Fitness and Nutrition
  • Population management and risk stratification
  • Healthcare Reform
  • The future of medicine – innovation and challenges
  • E-health care delivery
  • Homecare Aides, innovation, training and experiences
  • Patient care and quality
  • Preventive healthcare
  • Benefits Technology
  • Healthcare Consumerism
  • Revenue and cost strategies
  • And related care provider and payer topics are welcome

SUBMISSION GUIDELINES

All submissions will be handled electronically through the presentation submission form. The Program Committee will evaluate all submissions based on quality and relevance. Please submit the following details:

  • Complete contact information for speaker.
  • Short bio of the speaker.
  • 1 page abstract including an overview, description, and what attendees can expect from your session.
  • Learning objectives (at-least three).
    • Submissions

Workshop Program

Date: TBA

Session One (Payer and Provider), 9:00 am - 11:00 am

Tea/Coffee Break, 11:00 am - 11:30 am

Keynote, 11:30 am - 12:30 pm

Lunch Break, 12:30 pm - 2:00 pm

Session Two (ML Analytics), 2:00 pm - 4:00 pm

Tea/Coffee Break, 4:00 pm - 4:30 pm

Panel Discussion, 4:30 pm - 5:30 pm

Registration and Venue

Click Here to Register

Location

University of Washington - Magnuson Health Sciences Center 1959 NE Pacific St , Seattle, WA 98195

Sponsors

Interested in becoming a sponsor? Contact us via the following link for more information:

Sponsorship Coordinator

Organizers

SHANU SUSHMITA

Shanu Sushmita is a Postdoctoral Research Scientist at Center for Data Science, UW Tacoma. She is also a senior research consultant for KenSci. Her research interests are in the area of Machine Learning, Healthcare analytics and Information Retrieval. She received her PhD in computer science from the University of Glasgow, UK in 2012, and Bachelors in Engineering from the North Maharashtra University 2004. Her current research focus on providing machine-learning solutions in healthcare.

ANKUR TEREDESAI

Ankur M. Teredesai is a Professor of Computer Science & Systems, and Graduate Program Coordinator at the Institute of Technology, University of Washington Tacoma. His research interests focus on data science principles for societal impact and social good. His recent applied research contributions include risk prediction for heart failure and ACO cost prediction in healthcare analytics, trust-enhanced recommendations, distributed data mining algorithms for big data, novelty detection in video, and dietary volume estimation, to name a few. Teredesai heads the UW Center for Data Science, and serves as the Information Officer for ACM SIGKDD (Special Interest Group in Knowledge Discovery and Data Mining).

MARTINE DE COCK

Martine De Cock holds a M.Sc. and a Ph.D. degree in Computer Science from Ghent University (Belgium). She is an associate professor at the Institute of Technology, University of Washington Tacoma (USA), as well as a guest professor at Ghent University. Her previous work experiences include positions as a research assistant and a postdoctoral fellow supported by the Fund for Scientific Research - Flanders, a visiting scholar in the BISC group at the University of California, Berkeley (USA), a visiting scholar at the Knowledge Systems Laboratory at Stanford University (USA), and an associate professor at the Department of Applied Mathematics, Computer Science and Statistics at Ghent University. She has over 150 peer reviewed publications in international journals and conferences on artificial intelligence, data mining, machine learning, information retrieval, web intelligence and logic programming. She is a program committee member of numerous international conferences and an associate editor of IEEE Transactions on Fuzzy Systems. She co-organized the KDDCup2013. Her current research interests are secure machine learning, social networks, and data analytics to improve the quality of healthcare. She is a partner in N2N: A Ghent University Center of Excellence in Bioinformatics.

YING LI

Dr. Ying Li is the Chief Data Scientist at Jobaline.com, before which she founded EV Analysis Corporation after her career at Microsoft where she initiated and successfully built services, products, and teams with strong expertise in data mining and machines learning. Dr. Li is the winner of the 2012 ACM SIGKDD award for her outstanding contributions to the data mining field. She has filed and holds over 70 patent applications in the area of data mining, machine learning, computational advertising, software performance optimization, computer program tracing, profiling, and analysis. Dr. Li holds a Ph.D. degree in Computer Science from University of British Columbia, Canada, and MS and BS degrees in Applied Mathematics from Beijing University, China.

BHAUMIK CHOKSHI

Bhaumik has over eight years of experience in data science at Microsoft. He helped improve relevance of targeted advertising, through experimentation with various user intent signals. He also led a data science team focused on ad product recommendation and consumer ad experience measurement. As part of Windows Store team, he helped reduce app certification cost while maintaining quality of the app catalog. Bhaumik also worked on cloud infrastructure, supply optimization and operations related analytics. Recently, he has been working on marketing related analytics for Microsoft devices. For past one year, he has been one of the coordinators for SIGKDD Seattle chapter.

KENNY HERRINGTON

Math, data analysis and science have been a passion for Kenny for most of his adult life. He has almost a decade of technology industry experience in software development (Microsoft and more recently Amazon.com), and prior to that, many more years within the medical industry as an RN and MT (ASCP). He enjoys working on mathematical and computational programming based problems, as well as topics into computer vision, machine learning, and physics.

SYED FAHAD ALLAM SHA

Fahad has been associated with Microsoft working as a data scientist for more than four years. He received his PhD from UCF in social network mining. He has served as officer for the Seattle SIGKDD chapter since 2014; has been involved with the research community serving as the program committee for FLAIRS since 2011; and was a reviewer for IEEE Transactions on Computational Intelligence & AI in Games 2011, and a subreviewer for KDD 2012 and CIKM 2013 conferences.

JUN YUAN

Dr. Jun Yuan is an Associate Technical Fellow with the Boeing Company. He has more than 20 years’ experience in managing and conducting R&D projects in the areas of large scale data management, data analytics, and data semantic interoperability. He has been playing a leading role in many Boeing R&D projects and government research contracts. His recent research focus is the big data analytics. Dr. Yuan has 5 US patents awarded and 5 US patents pending, along with 30+ publications in his research area. Prior to joining the Boeing Company, he has held faculty positions in the Florida International University, Hong Kong University of Science and Technology, and Southeast University, China respectively.