****** New Paper Submission Deadline: September 19, 2016 ******
Important Dates:
Paper submission deadline (extended): September 19, 2016
Notification of acceptance: October 15, 2016
Camera ready paper due: November 20, 2016
Workshop: December 4, 2016
Submission Guidelines: https://sites.google.com/site/iwprha3/call-for-papers
Contact: Faisal Farooq (ffarooq@us.ibm.com)
Health care industry is very rapidly evolving mostly driven by overarching goals of cost reduction and improvement in quality of care. With growing costs and rising populations comes an inevitable paradigm shift towards accountable care where organizations are focusing on cost reduction, standardized care and quality improvement like never before. In addition, with the information overload in clinical literature coupled with the difficulty in extrapolating evidence from clinical trials to real world settings, providers find it difficult to select appropriate therapy for each patient. There is strong focus in health care in improving operational performance and adopting technology-enabled process improvements. In addition the hard boundaries between entities like care providers, payers and life sciences organizations are slowly giving way to increased collaboration and shift in roles duly enabled by sharing of real world practices and operational data.
It is possible to address many of these challenges by emulating and implementing best practices in health care by analyzing large amount of available information (extensive electronic health records recording patient conditions, diagnostic tests, labs, imaging exams, genomics, proteomics, treatments, outcomes, claims, financial records, clinical guidelines and best practices etc.). This data contains tremendously valuable hidden information relevant both for clinical and non-clinical decision support. At the heart of healthcare analytics is the ability to recognize (identify, classify and discover) patterns from the plethora of information available. As such, pattern recognition plays a pivotal role in the future of healthcare, specifically in healthcare analytics. The purpose of this workshop is to bring together pattern recognition and healthcare researchers interested in healthcare analytics and applications of pattern recognition in this field. The workshop program will consist of presentations by invited speakers from both pattern recognition and healthcare and by authors of papers submitted to the workshop. In addition, there will be a panel discussion to identify important problems, applications and synergies between pattern recognition and healthcare analytics disciplines. The intended audience of the workshop includes pattern recognition researchers interested in solving healthcare analytics problems, as well as the healthcare community in general including payers, providers and researchers.
3rd International Workshop on Pattern Recognition for Healthcare Analytics
https://sites.google.com/site/iwprha3/home
December 4, 2016
https://sites.google.com/site/iwprha3/home
December 4, 2016
Co-located with ICPR 2016 (http://www.icpr2016.org/site/)
****** New Paper Submission Deadline: September 19, 2016 ******
Important Dates:
Paper submission deadline (extended): September 19, 2016
Notification of acceptance: October 15, 2016
Camera ready paper due: November 20, 2016
Workshop: December 4, 2016
Submission Guidelines: https://sites.google.com/site/iwprha3/call-for-papers
Contact: Faisal Farooq (ffarooq@us.ibm.com)
Health care industry is very rapidly evolving mostly driven by overarching goals of cost reduction and improvement in quality of care. With growing costs and rising populations comes an inevitable paradigm shift towards accountable care where organizations are focusing on cost reduction, standardized care and quality improvement like never before. In addition, with the information overload in clinical literature coupled with the difficulty in extrapolating evidence from clinical trials to real world settings, providers find it difficult to select appropriate therapy for each patient. There is strong focus in health care in improving operational performance and adopting technology-enabled process improvements. In addition the hard boundaries between entities like care providers, payers and life sciences organizations are slowly giving way to increased collaboration and shift in roles duly enabled by sharing of real world practices and operational data.
It is possible to address many of these challenges by emulating and implementing best practices in health care by analyzing large amount of available information (extensive electronic health records recording patient conditions, diagnostic tests, labs, imaging exams, genomics, proteomics, treatments, outcomes, claims, financial records, clinical guidelines and best practices etc.). This data contains tremendously valuable hidden information relevant both for clinical and non-clinical decision support. At the heart of healthcare analytics is the ability to recognize (identify, classify and discover) patterns from the plethora of information available. As such, pattern recognition plays a pivotal role in the future of healthcare, specifically in healthcare analytics. The purpose of this workshop is to bring together pattern recognition and healthcare researchers interested in healthcare analytics and applications of pattern recognition in this field. The workshop program will consist of presentations by invited speakers from both pattern recognition and healthcare and by authors of papers submitted to the workshop. In addition, there will be a panel discussion to identify important problems, applications and synergies between pattern recognition and healthcare analytics disciplines. The intended audience of the workshop includes pattern recognition researchers interested in solving healthcare analytics problems, as well as the healthcare community in general including payers, providers and researchers.
rogério de paula, Ph.D.
Sr. Research Scientist
Visual Analytics & Comprehension Research Manager
Visual Analytics & Comprehension Research Manager
IBM Research | Brazil - BRL
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