Objectives
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.
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 consist of welcome session, keynote and invited talks, full/short paper presentations, demos, posters, and one or two panel discussion.
Submission requirements
We invite researchers and industrial practitioners to submit their original contributions following the AAAI format through EasyChair. Three categories of contribution are sought: full-research papers up to 8 pages; short paper up to 4 pages; and posters and demos up to 2 pages.
Research papers should demonstrate a novel computational theories or methodologies for addressing issues in health and healthcare. Papers discussing systems and applications should explain the development, implementation or evaluation of innovative tools and systems with potential benefits to solve problems in healthcare. Short papers should report works-in-progress, system descriptions, qualified opinions, positions, or recommendations on emerging topics.
Each paper will be reviewed by at least three reviewers from the program committee. The submitted research papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing.
Important Dates
October 27, 2017: Submissions due *** EXTENDED - FIRM DEADLINE ***
November 14, 2017: Notification of acceptance
November 20, 2017: Camera-ready copy due to AAAI
February 2-3, 2018: W3PHIAI'17 Workshop Program
Proceedings
All accepted papers will appear in the AAAI 2018 Workshops Proceedings.
Journal Publication Opportunity
A selected number of papers presented at the workshop will have opportunity to appear in the "Population and Personalized Health Intelligence" collection in the Journal of Digital Medicine, published by Nature, subject to further review
