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ACM SIGMM Interest List <[log in to unmask]>
Tue, 12 May 2020 14:15:08 +0200
Fulvio Frati <[log in to unmask]>
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Fulvio Frati <[log in to unmask]>
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*** IEEE Big PHP 2020 ***


[Apologies if you receive multiple copies of this CfP]


The Second IEEE SERVICES Workshop on Big Data for public health policy

In conjunction with the IEEE SERVICES 2020, October 19-23, 2020, Beijing,



As acknowledged by the World Health Organization, by a number of
governmental institutions, and patient associations, the effective
management of health-related problems depends on and requires appropriate
public health policies. A public health policy may have a significant effect
on the prevention and early diagnosis and early treatment of several diffuse
and debilitating conditions including, for instance, cognitive decline. On
the other hand, health policies can be also focused to target personalized
medicine and home healthcare, exploiting the knowledge obtained from the
collectivity tuning it for a specific situation.

The management of such health problems and their consequences through public
health policies can benefit from the analysis of heterogeneous data (e.g.,
collected from modern IoT sensors as well as from standard clinical trials).

Big Data Analytic techniques enable the investigation of specific health
problems, their possible relations to other comorbidities and contextual
factors, and patterns of such relations. 

The workshop seeks submissions from academia and industry presenting novel
research on all theoretical and practical aspects concerning the adoption of
Big Data Analytics in the context of evidence-based public health policy
making. The workshop targets innovative techniques and solutions for
supporting policy makers and clinicians in: i) taking decisions based on
evidence and on ii) simulating scenarios aimed at predicting evolutions of
health diseases at epidemiological level. It also aims to investigate
security and privacy concerns related to the analysis of health data and the
possible impact that security and privacy measures may produce on the
achievable quality of analyses and the effectiveness of health policies. The
workshop aims also to investigate: i) the modelling and adoption of advanced
Artificial Intelligence models for policy making based on simulations and
open data and ii) the possible trade-off between the design and
implementation of health policies that may require years to produce their
expected results and solutions able to rapidly produce tangible results. 

The workshop will bring together researchers of different disciplines,
policy makers and clinicians, from academia and industry, all sharing a
common goal: to go beyond the frontier of today's public health policy
making process by envisioning how to exploit the full potential of Big Data
Analytics in ways compliant with the principles and needs of modern
societies, like satisfying security and privacy requirements.

Topics for the workshop include, but are not limited to: 

-          Data driven public health policy making models 

-          Model based Big data solutions for health-related policy making 

-          Decision support systems for clinicals and policy making 

-          Innovative Big Data as a service architecture for health 

-          Security aspects of Big Data analytics threating sensible data

-          Privacy aware Big Data models and analytics in health scenarios

-          AI models for health-related policy making

-          Mixing simulations and open data for health policies predictions

-          Advanced reaction-oriented policy models for health

-          IOT sensing capabilities for health

-          IOT sensing and policies for personalized medicine




Workshop Chairs:

- Marco Anisetti, Università degli Studi di Milano, Italy

- George Spanoudakis, City University of London, UK




We call for original and unpublished papers no longer than 6 pages (up to 2
additional pages may be purchased subject to approval by the Publication
Chair.). All papers will be reviewed with a minimum of 3 good-quality
reviews per paper. The manuscripts should be formatted in standard IEEE
camera-ready format (double-column, 10-pt font) and be submitted as PDF
files (formatted for 8.5x11-inch paper). The submission URL is: 


Authors wishing to submit a paper to this workshop must select the track
entitled “IEEE SERVICES Workshop on Big Data for public health policy
making” in order to be considered.


Important Dates


- Paper Submission Deadline: June 12, 2020

- Notification to Author: July 3, 2020

- Camera-ready & Registration: July 20, 2020


For general questions about this workshop, please contact either workshop


- Marco Anisetti at: [log in to unmask]
<mailto:[log in to unmask]>  

- George Spanoudakis at: [log in to unmask]
<mailto:[log in to unmask]>