posted by organizer: kalogridis || 1537 views || tracked by 12 users: [display]

HealthDENSE 2015 : IEEE CAMAD 2015 : Special Session on Healthcare Data Mining in Sensor Networks (HealthDENSE)

FacebookTwitterLinkedInGoogle

Link: http://www.ieee-camad.org/
 
When Sep 7, 2015 - Sep 9, 2015
Where University of Surrey, Guildford, UK
Submission Deadline Jun 15, 2015
Notification Due Jul 10, 2015
Final Version Due Aug 1, 2015
Categories    data mining   healthcare   sensor networks   anomaly detection
 

Call For Papers

The societal challenge to improve proactive healthcare and community services through technological advances in the Internet of Things (IoT), calls for granular and continuous nationwide instrumentation, driven by data mining technologies.

Example healthcare challenges include behaviour and lifestyle-related diseases, such as obesity, depression, work-related stress, stroke, falls and cardiovascular health issues. A paradigm shift from a reactive towards a proactive model, is of paramount importance for the sustainability of healthcare costs of an ageing population (e.g. in the UK and Japan). In this direction, mobile healthcare sensors manifest a promising engineering approach to the problem. For example a data fusion of environmental and wearable biosensors, such Electrocardiogram (ECG), accelerometer, global positioning (GPS), can help detect medical emergencies such falls and strokes, analyse longer-term illnesses such as depression and anxiety, intervene, e.g. with visualisation-based therapies, or gather more data, e.g. with application-aided mood collection or crowdsourcing.

One enabling technology to healthcare data mining involves centralised (big) data mining. However, continuous and real-time mobile communications of healthcare sensor data are limited by energy (battery) and bandwidth physical constrains. Instead, the aim of this CAMAD 2015 Special Session on Healthcare Data mining in sENSor nEtworks (HealthDENSE) is to advance recent research of sensor-based healthcare data mining. This involves, in-network activity and behaviour analytics, time-series data mining, and delay-tolerant communications. The scope of HealthDENSE further extends to knowledge-based network optimisation through sensor data mining. Finally, recent advances on data mining for privacy protection can be adopted and adapted for e-health citizen privacy.

Submission of original and unpublished work in all areas related to HealthDENSE is welcome. Topics of interest include, but are not limited to, the following areas.
* In-network or sensor data mining.
* Time series data fusion.
* Behaviour analytics.
* Distributed symptom detection model for learning and inference.
* Mood and stress-related analytics.
* Anomaly detection in ECG and activity data.
* Healthcare mobile ad hoc network simulation.
* Knowledge-based wireless network optimisation for e-health.
* Healthcare data offloading and delay-tolerant networks.
* Sensor health-aware routing.
* Data mining for e-health privacy protection.

HealthDENSE’15 Chair and Organiser:
---------------------------------------
Dr Georgios Kalogridis
Principal Research Engineer & Team Leader
Toshiba Research Europe Limited
Telecommunications Research Laboratory
32 Queen Square, Bristol, BS1 4ND, UK
Email: george@toshiba-trel.com

Related Resources

DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
ECML-PKDD 2017   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery
ICDM 2017   IEEE International Conference on Data Mining 2017
IEEE ITOEC 2017   2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference
KDD 2017   Call for Research Papers
IEEE ITNEC 2017   2017 IEEE 2nd Information Technology,Networking,Electronic and Automation Control Conference
cluster17   IEEE CLUSTER
ISMIS 2017   23rd International Symposium on Methodologies for Intelligent Systems
PervasiveHealth 2017   Pervasive Computing Technologies for Healthcare
EIS 2017   SPECIAL SESSION on EHEALTH INFORMATION SYSTEMS