****** The 2nd AAAI Workshop on Health Intelligence (W3PHIAI-18) ******

****** In conjunction with the 32nd AAAI Conference on Artificial Intelligence (AAAI-18) on Feb 2–3, 2018, in New Orleans, Louisiana, USA ******


This workshop will address various aspects of using AI for improving population and personalized healthcare and is structured in two tracks focusing on population (W3PHI) and personalized health (HIAI). Following the success of AAAI-W3PHI 2014-16, AAAI-HIAI 2013-16, and the first joint workshop at AAAI-17 (W3PHIAI-17), this workshop aims to bring together a wide range of computer scientists, clinical and health informaticians, researchers, students, industry professionals, national and international health and public health agencies, and NGOs interested in the theory and practice of computational models of population health intelligence and personalized healthcare to highlight the latest achievements in the field. The workshop promotes open debate and exchange of opinions among participants.
Workshop Description Public health authorities and researchers collect data from many sources and analyze these data together to estimate the incidence and prevalence of different health conditions, as well as related risk factors. Modern surveillance systems employ tools and techniques from artificial intelligence and machine learning to monitor direct and indirect signals and indicators of disease activities for early, automatic detection of emerging outbreaks and other health-relevant patterns. To provide proper alerts and timely response public health officials and researchers systematically gather news, and other reports about suspected disease outbreaks, bioterrorism, and other events of potential international public health concern, from a wide range of formal and informal sources. Given the ever-increasing role of the World Wide Web as a source of information in many domains including healthcare, accessing, managing, and analyzing its content has brought new opportunities and challenges. This is especially the case for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. Web applications along with text processing programs are increasingly being used to harness online data and information to discover meaningful patterns identifying emerging health threats. The advances in web science and technology for data management, integration, mining, classification, filtering, and visualization has given rise to a variety of applications representing real time data on epidemics.
Moreover, to tackle and overcome several issues in personalized healthcare, information technology will need to evolve to improve communication, collaboration, and teamwork between patients, their families, healthcare communities, and care teams involving practitioners from different fields and specialties. All of these changes require novel solutions and the AI community is well positioned to provide both theoretical- and application-based methods and frameworks. The goal of this workshop is to focus on creating and refining AI-based approaches that (1) process personalized data, (2) help patients (and families) participate in the care process, (3) improve patient participation, (4) help physicians utilize this participation in order to provide high quality and efficient personalized care, and (5) connect patients with information beyond those available within their care setting. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of “generic” therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions.


*** Topics ***

The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, network theory, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in population and personalized health. The scope of the workshop includes, but is not limited to, the following areas:

• Knowledge Representation and Extraction
• Integrated Health Information Systems
• Patient Education
• Patient-Focused Workflows
• Shared Decision Making
• Geographical Mapping and Visual Analytics for Health Data
• Social Media Analytics
• Epidemic Intelligence
• Predictive Modeling and Decision Support
• Semantic Web and Web Services
• Biomedical Ontologies, Terminologies, and Standards
• Bayesian Networks and Reasoning under Uncertainty
• Temporal and Spatial Representation and Reasoning
• Case-based Reasoning in Healthcare
• Crowdsourcing and Collective Intelligence
• Risk Assessment, Trust, Ethics, Privacy, and Security
• Sentiment Analysis and Opinion Mining
• Computational Behavioral/Cognitive Modeling
• Health Intervention Design, Modeling and Evaluation
• Online Health Education and E-learning
• Mobile Web Interfaces and Applications
• Applications in Epidemiology and Surveillance (e.g. Bioterrorism, Participatory Surveillance, Syndromic Surveillance, Population Screening)



*** Format ***

The workshop will be two full days consisting of a welcome session, keynote and invited talks, full/short paper presentations, demos, posters, and one or two panel discussions.



*** Submission requirements ***

We invite researchers and industrial practitioners to submit their original contributions following the AAAI format through EasyChair. Three categories of contributions are sought: full-research papers up to 8 pages; short paper up to 4 pages; and posters and demos up to 2 pages.

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*** Proceedings ***

All accepted papers will appear in the AAAI 2018 Workshops Proceedings. We will tentatively invite the best submissions to extend their papers in order to be published in a special issue of a reputable journal in the field.



*** Important Dates ***

October 20, 2017: Submissions due
November 10, 2017: Notification of acceptance
November 20, 2017: Camera-ready copy due to AAAI
February 2-3, 2018: W3PHIAI'17 Workshop Program



*** Workshop Organizing Committee ***


Martin Michalowski, PhD (Co-chair)
University of Minnesota,
School of Nursing
2-139 Weaver-Densford Hall, 308 Harvard Street SE, Minneapolis, MN 55455
email: martinm@umn.edu
url: https://www.nursing.umn.edu/bio/faculty-staff/martin-michalowski


Arash Shaban-Nejad, PhD, MPH (Co-chair)
The University of Tennessee Health Science Center - Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics,
Department of Pediatrics,
50 N Dunlap Ave, Memphis, TN 38103, USA
(901) 287-5836 (tel)
email: ashabann@uthsc.edu
url: https://academic.uthsc.edu/faculty/facepage.php?netID=ashabann&personnel_id=343203


Szymon Wilk, PhD
Division of Intelligent Decision Support Systems,
Faculty of Computing Science,
Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
email: szymon.wilk@cs.put.poznan.pl


David L. Buckeridge, MD, PhD
McGill Clinical & Health Informatics,
McGill University
1140 Pine Avenue West,
Montreal, Quebec, H3A 1A3 CANADA,
(514) 398-8355 (tel)
(514) 843-1551 (fax)
email: david.buckeridge@mcgill.ca
url: http://surveillance.mcgill.ca/


John S. Brownstein, PhD
Boston Children's Hospital,
Harvard University,
Autumn St, Room 451,
Boston, MA 02215 USA,
(617) 355-6998 (tel)
(617) 730-0921 (fax)
email: john_brownstein@harvard.edu
url: http://chip.org/john-brownstein


Byron C. Wallace, PhD
College of Computer and Information Science,
Northeastern University,
360 Huntington Ave. Boston, Massachusetts, Boston, MA 02115, USA
email: byron@ccs.neu.edu
url: http://byronwallace.com


Michael J. Paul, PhD
Department of Information Science,
The university of Colorado Boulder,
Environmental Design 201315 UCB,
1060 18th Street Boulder, CO 80309, USA
email: mpaul@colorado.edu
url: http://cmci.colorado.edu/~mpaul/



Workshop URL: http://w3phiai2018.w3phi.com/