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--- teaam:start [2019/03/01 09:23] – first cfp gjn
+++ teaam:start [2019/05/30 19:03] – [Important Dates] gjn
@@ Line 4: / Line 4: @@
 Chairs: [[http://gjn.re|Grzegorz J. Nalepa]], [[http://www.ri.fzv.um.si/gstiglic/|Gregor Stiglic]], [[http://islab.hh.se/slanow|Sławomir Nowaczyk]], [[https://webs.um.es/jmjuarez|Jose M. Juarez]], [[http://www.cs.put.poznan.pl/jstefanowski/|Jerzy Stefanowski]]
+{{ :teaam:aime2019teaam-cfp2.pdf |Call for papers}}
 ===== Organizers =====
@@ Line 20: / Line 23: @@
   * interpretable machine learning in medical applications
   * explanatory user interfaces and human computer interaction for explainable AI
+  * consequences of black-box AI systems in medicine
   * ethical aspects, law and social responsibility
   * emotion-based personalization and affective computing solutions in medicine
   * human-oriented adaptation in medical systems
-  * patient behaviour change detection
+  * patient behaviour change detection and explanation transparency in person-centered health care
-  * person-centered health care
+  * context-aware interpretable medical systems
-  * context-aware medical systems
+  * empowering patients and self-management through understandable AI
-  * empowering patients and self-management
-  * consequences of black-box AI systems in medicine
 ===== Motivation =====
-The investment and development of AI in the clinical field offers huge societal benefits in the current era of digital medicine, with a significant amount of data around healthcare processes captured in the form of Electronic Health Records, health insurance claims, medical imaging databases, disease registries, spontaneous reporting sites, clinical trials, etc. This positive impact is put under the spotlight regarding the medical responsibilities, the potentially harmful use, the emerging interest in the regulation of algorithms and the need of explanations. Predictive modeling becomes increasingly necessary for both data analysts and healthcare professionals, as it offers unique opportunities for deriving healthcare insights. At the same time, these opportunities come with significant dangers and risks that are unlike anything we have seen in the past. This controversial discussion provides a number of research challenges such as: 1) Line regarding interpretability in Machine Learning/AI, 2) Line regarding affective AI in medicine, 3) Data safety - patient data are highly sensitive and require appropriate safety measures and regulation, 4) Data heterogeneity - medical data comes in many forms including: structured, unstructured, text, images, continuous signals from sensors, etc., 5) Sparsity, imperfectness and data gaps – patient records maybe sparse due to infrequent clinical visits, and often, data are not equally collected at each medical encounter as well as they are affected by various  sources of imperfectness.
+The investment and development of AI in the clinical field offers huge societal benefits in the current era of digital medicine, with a significant amount of data around healthcare processes captured in the form of Electronic Health Records, health insurance claims, medical imaging databases, disease registries, spontaneous reporting sites, clinical trials, etc. This positive impact is put under the spotlight regarding the medical responsibilities, the potentially harmful use, the emerging interest in the regulation of algorithms and the need of explanations. Predictive modeling becomes increasingly necessary for both data analysts and health care professionals, as it offers unique opportunities for deriving health care insights. At the same time, these opportunities come with significant dangers and risks that are unlike anything we have seen in the past. This controversial discussion provides a number of research challenges such as: 1) interpretability in Machine Learning/AI, 2) affective AI in medicine, 3) Data safety - patient data are highly sensitive and require appropriate safety measures and regulation, 4) Data heterogeneity - medical data comes in many forms including: structured, unstructured, text, images, continuous signals from sensors, etc., 5) Sparsity, imperfectness and data gaps – patient records maybe sparse due to infrequent clinical visits, and often, data are not equally collected at each medical encounter as well as they are affected by various  sources of imperfectness.
-===== Format =====
-The proposed workshop will include paper presentations and invited talks related to the workshop topics listed above, as well as a panel discussion. All submitted papers will be subject to a review by the workshop Program Committee . Based on the number of high quality submissions we will define the length of the presentations that will be followed by time for questions and discussion from the audience.
-===== Proceedings =====
+===== Schedule =====
-We are aiming at proving CEUR WS proceedings containg all the papers presented at the workshop. Furthermore, we are considering a proposal of a special issue of a JCR journal.
-===== Program Committee =====
-(tentative)
-Martin Atzmueller, Univeristy of Tilburg, The Netherlands
+{{:teaam:mgrzegorzek-photo.jpg?150 |}}
+**Keynote speaker:** Prof. Marcin Grzegorzek, Universität zu Lübeck, Institut für Medizinische Informatik
-Piotr Augustyniak, AGH University of Science and Technology, Poland
+**Title:** //Human-centred Pattern Recognition for Assistive Health Technologies//
-Hendrik Blockeel, Katholieke Universiteit Leuven, Belgium
+**Abstract:** We live in a data-driven society and significantly contribute to this concept by voluntarily generating terabytes of data everyday. Pattern recognition algorithms that automatically analyse and interpret that huge amount of heterogeneous data towards prevention (early risk detection), diagnosis, assistance in therapy/aftercare/rehabilitation as well as nursing have achieved an extremely high scientific, societal and economic importance. In this talk, Marcin Grzegorzek will present his research in the area motivated above considering, apart from machine learning, aspects of hardware, participatory design and ELSI (Ethical, Legal and Social Implications). Two of Marcin's projects, (1) Cognitive Village: Adaptively Learning Technical Support Platform for Elderly (funded by the German Federal Ministry of Education and Research) and (2) My-AHA: My Active and Healthy Ageing (EC Horizon 2020), will serve as concrete application scenarios.
-Jerzy Błaszczyński, Poznań University of Technology, Poland
+===== Proceedings =====
+We are aiming at proving CEUR WS proceedings containg all the papers presented at the workshop. Furthermore, we are considering a proposal of a special issue of a JCR journal.
-David Camacho, Universidad Autonoma de Madrid, Spain
+===== Program Committee =====
+(tentative)\\
-Manuel Campos, University of Murcia, Spain
+Martin Atzmueller, Univeristy of Tilburg, The Netherlands\\
+Piotr Augustyniak, AGH University of Science and Technology, Poland\\
-Alex Freitas, University of Kent, United Kingdom
+Jerzy Błaszczyński, Poznań University of Technology, Poland\\
+David Camacho, Universidad Autonoma de Madrid, Spain\\
-Johannes Fürnkranz. TU Darmstadt, Germany
+Manuel Campos, University of Murcia, Spain\\
+Alex Freitas, University of Kent, United Kingdom\\
-Marcin Grzegorzek, Universität zu Lübeck, Germany
+Alejandro Rodríguez González, Universidad Politecnica de Madrid\\
+Marcin Grzegorzek, Universität zu Lübeck, Germany\\
-Giorgio Leonardi, University Piemonte Orientale, Italy
+Jean-Baptiste Lamy,  University Paris 13, France\\
+Giorgio Leonardi, University Piemonte Orientale, Italy\\
-Peter Lucas Leiden University, The Netherlands
+Helena Lindgren, Umeå University, Sweden\\
+Zachary Lipton, Carnegie Mellon University, USA\\
-Agnieszka Ławrynowicz, Poznań University of Technology, Poland
+Peter Lucas Leiden University, The Netherlands\\
+Agnieszka Ławrynowicz, Poznań University of Technology, Poland\\
-Erini Ntoutsi, Leibniz University Hannover, Germany
+Juan Carlos Nieves, Umeå University, Sweden\\
+Erini Ntoutsi, Leibniz University Hannover, Germany\\
-Jose Palma, University of Murcia, Spain
+Jose Palma, University of Murcia, Spain\\
+Niels Peek, University of Manchester, United Kingdom\\
-John F. Rauthmann, Universität zu Lübeck, Germany
+Petra Povalej Brzan, University of Maribor, Slovenia\\
+John F. Rauthmann, Universität zu Lübeck, Germany\\
-Spiliopoulou Otto-von-Guericke-University Magdeburg, Germany
+Myra Spiliopoulou, Otto-von-Guericke-University Magdeburg, Germany\\
+Stephen Swift, Brunel University, United Kingdom\\
+Allan Tucker, Brunel University, United Kingdom\\
+Cristina Soguero Ruiz, Universidad Rey Juan Carlos, Spain\\
 ===== Important Dates =====
-  * Paper submission:	2019-04-15
+  * Paper submission:	2019-04-29
   * Notification:		2019-05-13
-  * Camera-ready:	2019-06-10
+  * Camera-ready:	2019-05-31
-  * Workshop:		TBD
+  * Workshop:		2019-06-26-29
 ===== Paper submission =====
-A separate Easychair installation will be provided. Springer LNCS format of PDF submissions is required.
+The Easychair installation at https://easychair.org/conferences/?conf=teaam2019 shoud be used for submissions. We encourage full (12pp) as well as short (6pp) original research papers. Springer LNCS format of PDF submissions is required.