Expanding the Boundaries of Health Informatics Using Artificial Intelligence (HIAI 2013)
Welcome to the First Workshop on Expanding the Boundaries of Health Informatics Using Artificial Intelligence (HIAI)
Co-located with The Twenty-Seventh AAAI Conference (AAAI-13)
July 14-18, 2013 in Bellevue, Washington, USA
April 21st 2013 - Acceptance notifications have been sent to authors. We will be posting the program in May. Thanks to all authors for their high quality submissions.
March 31st 2013 - Per requests from several authors we have extended the submission date to Sunday April 7th.
March 5th 2013 - The workshop will be held on Monday, July 15th. See you in Bellevue.
Feb. 25th 2013 - AAAI has decided to extend the workshop paper submission deadline from March 28th to April 3rd. Our schedule has been updated accordingly.
Jan. 25th 2013 - Program Committee members added. Thank you to all the reviewers!
Jan. 15th 2013 - Dr. Mark Musen added to the program as the opening speaker
Jan. 4th 2013 - Website online
The rapid development and expansion of health informatics is demonstrated by the proliferation of electronic patient records and the transition to computer-based patient treatment tools and point-of-care informatics infrastructure. Accelerating its growth is the increasing availability of medical information such as evidence-based clinical guidelines and results of clinical studies including randomized control trials. Unfortunately, the rate of growth combined with improved data availability leads to health information overload that can severely impair clinical work and adversely affect health-related decision-making. AI techniques are very well suited to help overcome this problem and can facilitate advances in the health informatics area that can have a profound effect on patient outcomes. As such, a true opportunity exists to shape the future of healthcare systems through the application of AI to address a number of emerging health system problems.
AI techniques can help not only with collecting, organizing and storing volumes of personal and population data (including sensitive patient information), but also with analyzing data and information with the purpose of facilitating data-driven and evidence-based decision making. The latter can be achieved by identifying and presenting health practitioners with pertinent medical information and knowledge when it is needed. Challenges lie in both determining what is relevant medically and contextually, and when and in it what form it is appropriate to provide this information and knowledge. For example, presenting disease- and treatment-relevant information to a physician at the point of care during a patient encounter enables the development of decision support tools that lead to improved patient outcomes and has a positive societal impact. Developing (and deploying) intelligent health systems is a research area ripe for AI techniques where advances are needed to tackle real-world healthcare problems such as disease identification and management, drug-drug and drug-disease interaction, and patient education.
The purpose of the workshop is to bring together health informatics researchers working on AI research and AI researchers working on methodological research applied to health informatics, and for them to share results of their research.
This workshop focuses on AI-based methodological and application contributions in health informatics and its aim is to foster opportunities for collaborative research within a multi-discipline research community that offers expertise in medicine, bioinformatics, computer and information science. Topics of interest are divided into two key themes (but not limited to):
A. Health knowledge - discovery, management and use
1. Knowledge discovery in medical data using data mining
2. Natural language processing and information retrieval for textual resources
3. Knowledge engineering and management using biomedical ontologies
4. Clinical decision making and reasoning, including case-based reasoning and clinical practice guidelines (CPGs)
5. Personalization of patient care
B. Intelligent health systems
1. Clinical decision support systems (CDSS)
2. Multi-agent health systems
3. Telemedicine and consumer health informatics
4. Assisted living environments
The program of the one-day workshop will begin with an opening talk by Dr. Mark Musen. The remainder of the presentations will be divided into two sessions organized around the two themes defined above, and the program will conclude with a panel discussion. The first session will focus on methodological papers centered around health knowledge. It will start with an invited talk given by Dr. Barry O'Sullivan on the challenges and opportunities for applying constraint programming to gaining health knowledge. The other section will look at intelligent health systems and it will begin with an invited talk by Dr. Jay M. Tenenbaum describing opportunities to apply human and machine intelligence to organize and refine the world's knowledge about treating cancer. The talk will discuss AI topics for medicine including text mining, machine learning, crowdsourcing and others, and it will update his work on Cancer Commons presented at his keynote IAAI'10 talk and in the AI magazine article "Cancer: A Computational Disease that AI Can Cure". A summarizing discussion panel will provide an opportunity for attendees to ask questions of and share their thoughts with invited panel experts on the topic of "AI and the Personalization of Patient Care: Challenges and Solutions".
Please submit all papers via EasyChair.
Potential participants are invited to submit either a full-length technical paper or a short position or demonstration paper. Technical papers must be no longer than six (6) pages in length, including references and figures. Short submissions can be up to 4 pages in length and describe a position on a topic of the workshop or a demonstration/tool. Submissions are accepted in PDF format only, using the AAAI formatting guidelines and including author names.
Additionally, selected submissions will be invited to submit an extended version of their work to a proposed journal special track on AI in Health.
Martin Michalowski, Chair (Adventium Labs, email@example.com)
Wojtek Michalowski, Co-chair (University of Ottawa)
Dympna O'Sullivan, Co-chair (City University London)
Szymon Wilk, Co-chair (Poznan University of Technology)
- Jose Luis Ambite, Information Sciences Institute, University of Southern California, USA
- Naveen Ashish, University of California-Irvine, USA
- David Buckeridge, McGill University, Canada
- Chris Buckingham, Aston University, UK
- Yao-Yi Chiang, Information Sciences Institute, University of Southern California, USA
- Karen Church, Telefonica Barcelona, Spain
- Jacomo Corbo, Telfer School of Management, University of Ottawa, Canada
- Jesse Davis, Katholieke Universiteit Leuven, Belgium
- Julie Doyle, CASALA, DKIT, Ireland
- Aniko Ekart, Aston University, Birmingham, UK
- Dan Goldberg, Texas A&M University, USA
- Philip Gooch, Kings College London, UK
- William Klement, University Health Network , University of Toronto, Canada
- Andrey Kolobov, University of Washington, USA
- Krzysztof Krawiec, Poznan University of Technology, Poland
- Stan Matwin, Dalhousie University, Canada
- Matt Michelson, InferLink, USA
- Jerzy Stefanowski, Poznan University of Technology, Poland
- Simone Stumpf, City University London, UK
- Xing Tan, University of Ottawa, Canada
- Peter Weller, City University London, UK
- David Wilson, University of North Carolina at Charlotte, USA
Questions concerning the workshop should be addressed to Martin Michalowski at firstname.lastname@example.org