Subject: | [WI] [CFP] The 2nd IEEE SERVICES Workshop on Big Data for public health policy making |
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Date: | Tue, 12 May 2020 14:12:56 +0200 |
From: | Fulvio Frati <fulvio.frati@unimi.it> |
Reply-To: | Fulvio Frati <fulvio.frati@unimi.it> |
To: | wi@lists.uni-karlsruhe.de |
*** IEEE Big PHP 2020
***
[Apologies if you
receive multiple copies of this CfP]
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The Second IEEE SERVICES
Workshop on Big Data for public health policy making
In conjunction with the
IEEE SERVICES 2020, October 19-23, 2020, Beijing, China
https://conferences.computer.org/services/2020/workshops/bigphp2020.html
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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
Organization
Workshop Chairs:
- Marco Anisetti, Università degli Studi di
Milano, Italy
- George Spanoudakis,
City University of London, UK
Submission
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:
https://easychair.org/conferences/?conf=ieeeservices2020
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
organizer:
- Marco Anisetti at: marco.anisetti@unimi.it
- George Spanoudakis at:
G.E.Spanoudakis@city.ac.uk