CARE International Workshop Series
CARE 2019 - The Tenth International Workshop on Collaborative Agents Research & Development
CARE for Smarter Health
Part of the Joint Workshop on Autonomous Agents for Social Good
In collaboration with Strategic Reasoning for Societal Challenges (SRSC)
In conjunction with AAMAS-19, May 13-14, 2019, Montreal, Canada
WORKSHOP SUMMARY
Part of the Joint Workshop on Autonomous Agents for Social Good
In collaboration with Strategic Reasoning for Societal Challenges (SRSC)
In conjunction with AAMAS-19, May 13-14, 2019, Montreal, Canada
“CARE for Smarter Health” aims to discuss computational models, social computing, decision support systems, and agent-based technology, both theoretical models as well as research applied to practical solutions related to Healthcare and Medicine, including (non-exhaustive list):
-
Personalized Healthcare
-
Ethical Issues of AI and Health
-
Distributed Healthcare Systems
-
Social Computing in Healthcare
-
Decision support systems in Healthcare
-
Care for Chronic Conditions with AI Support
-
Deep Learning in Medicine
-
Medical Expert Systems
-
Care Team Coordination and Collaboration
-
Medical Robotics, Drones, Surgery, Prosthetics
-
Chatbots in Healthcare
-
Social Media Analysis for Epidemiology
The CARE workshop series promotes the research agenda around topics relevant to the future of the society aiming at novel technologies, translate research into industry, support new business and create new industries. The discussion will address questions such as: How to create and combine currently scientific paradigms and disruptive technologies that enable the next generation of solutions for challenging scenarios in health and socially-centred applications? How can we create computational models, representations, algorithms and protocols to enable the next generation of intelligent collaborative technologies? And finally, how to translate these advanced researches into industry solutions?
The half-day event will feature a mixture of invited talks, discussions and submitted contributions describing current work or work in progress in AI, agent and machine learning research and technology.
We conclude with a panel discussion around a proposed research agenda to advance the field of collaborative technology and healthcare, to foment the development of new technologies, support new business structures, and shape the academia-industry relationship.
KEYNOTE SPEECH
Prof. Dr. Christian Guttmann, "How Multi-Agent Systems and AI is a driving transformation force in Health Care"
Vice President, Global Head of AI, Tieto, Sweden; nominated a Top-100 AI Leaders in Drug Discovery and Advanced Healthcare, by Deep Knowledge Analytics (linkedin)
Artificial Intelligence offers substantial benefits to how we deliver health care and medicine. AI is becoming increasingly accurate and effective in performing a broad range of complex health care related tasks (e.g. recognizing a malignant tumour on MRIs, and coordinating care). Such AI driven performance can then be scaled up, improve health outcomes and save many lives. As a result, AI helps clinicians, patients and many health stakeholders to make faster, better, and cheaper decisions, at scale. This presentation provides an overview of the state of the art in how AI and MAS are shaping the health care journey forward.
Prof. Dr. Peter Sarlin, "Learnings from 100 AI projects: Implications for healthcare"
Executive Chairman and Chief Scientist of Silo.AI, Professor of Practice at Hanken School of Economics (linkedin)
The past few years have been dominated by the hyped possibilities of AI. Implications of AI are oftentimes vindicated by highlighting promising research with a promise of real-world value and a wide range of application areas that could be transformed. In today's discussion, a common trait is to focus on one or the other, but rarely on their combination. This talk summarizes learnings from 100 AI projects in terms of technological challenges and practical bottlenecks, as well as technology-enabled opportunities, to find the largest opportunities for value creation. This allows us also to mirror the current state of AI into application areas and specific opportunities in healthcare, as well as examples of ongoing transformative AI initiatives.
RESEARCH QUESTIONS
CARE for Smarter Health opens a forum to discuss innovation around AI, Computational Intelligence, decision support systems, and agent-based computing models and technologies that lead to collaborative approaches for pressing problems in the healthcare segment.
Topics of interest include:
-
How agent technology can help to analyse and act on vast amounts of complex data?
-
How to build a model of collaborative behaviour in practical applications?
-
How to build and incorporate Decision Support technology to advance Healthcare solutions?
-
How to combine Social Analytics and Social computing into Healthcare?
-
How organisational structures influence the negotiation of agents and the distribution/execution of tasks?
-
How to enable an effective communication infrastructure for collaborative interaction?
-
How to construct agent-based models of social behaviour, aiming to understand, model, and influence complex behaviour, group behaviour, and the impact of micro-macro actions upon the system?
-
How to deploy lifecycle management systems in real world applications, particularly healthcare.
-
How can we enable flexible, goal-driven and contextualised plan creation and business process management (including intelligent execution, monitoring, management, and optimization of business processes)?
-
How to build an effective monitoring-recognition-intervention framework in practical scenarios?
GENERAL CHAIRS
Dr. Fernando Koch^, IBM Global Services, USA
Dr. Andrew Koster, IIIA-CSIC & Universitat Autonoma de Barcelona, Spain
Prof. Dr. Christian Guttmann, University of New South Wales, Australia & Karolinska Institute & Nordic AI Institute & Tieto, Sweden
TECHNICAL PROGRAM COMMITTEE
Alessio Bottrighi, Dipartimento di Informatica, Università del Piemonte Orientale, Italy
Andrew Koster, IIIA-CSIC, Autonomous University of Barcelona, Spain
Apostolos Gotsias, University of the Aegean, Greece
Atsushi Yoshikawa, Tokyo Institute of Technology, Japan
Beatriz López, University of Girona, Italy
Christian Guttmann, Nordic AI Institute, Karolinska Institute, TIETO, Sweeden
Clare Martin, Oxford Brookes University, UK
Dongwen Wang, Arizona State University, USA
Fernando Koch, IBM Global Services, USA
Fumihiro Sakahira, KOZO KEIKAKU ENGINEERING Inc., Japan
Hugo Paredes, INESC TEC and UTAD, Portugal
Ingo J. Timm, University of Trier, Germany
Isabelle Bichindaritz, State University of New York at Oswego, USA
Jianqi An, China University of Geosciences, China
Jinhua She, Tokyo University of Technology, Japan
Klaus-Dieter Althoff, DFKI / University of Hildesheim, Germany
Luca Anselma, Università di Torino, Italy
Luigi Portinale, Universita' del Piemonte Orientale "A. Avogadro", Italy
Manfred Reichert, University of Ulm, Germany
Masanori Fujita, Tokyo Institute of Technology, Japan
Michael Ignaz Schumacher, University of Applied Sciences Western Switzerland (HES-SO), Switzerland
Michel Dojat, INSERM, France
Néstor Darío Duque Méndez, Universidad Nacional de Colombia, Colombia
Nirmalie Wiratunga, The Robert Gordon University, UK
Petra Perner, Institute of Computer Vision and Applied Computer Sciences, Germany
Rainer Schmidt, University of Rostock, Germany
Sadiq Sani, Robert Gordon University Aberdeen, UK
Sara Montagna, Università di Bologna, Italy
Satoshi Takahashi, Tokyo University of Science, Japan
Shihan Wang, University of Amsterdam, Netherlands
Tiago Primo, Federal University of Pelotas, Brazil
Tilman Dingler, The University of Melbourne, Australia
Vassilis Koutkias, Institute of Applied Biosciences, Centre for Research and Technology Hellas, Greece
Vinicius Renan de Carvalho, University of São Paulo, Brazil
Yeunbae Kim, Institute for Information and Communication Technology Promotion, South Korea