SPECIALSESSIONSMEDICAL AND HEALTHCARE APPLICATIONSOF EVOLUTIONARY COMPUTATION
Ivanoe De Falco, Antonio Della Cioppa, Umberto Scafuri,Ernesto Tarantino

Evolutionary Computation methods are being more and more frequently used to facechallenging problems in Medicine and HealthCare.
These methods can be of great help in finding good solutions to many practical medical
and healthcare applications, as for example in tasks as disease screening, diagnosis,
treatment planning, prognosis, imaging, signal processing, healthcare management and anyother task related to machine learning, knowledge discovery, decision support, regression,forecasting, optimization, feature selection and data mining.
The Special Session aims to bring together international experts in evolutionary
computation for the exchange of ideas across disciplines encouraging multidisciplinary
research collaborations and the development of new concepts in the important and growing
domain of Medical and HealthCare ICT, thus creating a forum of excellence on the use ofevolutionary inspired methods to face medical and healthcare problems.
This increasing trend towards the use of Evolutionary Computation methods to facechallenging medical and healthcare problems in the next years, not only will a Special
Session on this topic be of immediate relevance, it will also provide a platform forencouraging implementations of evolutionary methods for solving problems in various
medical and healthcare specialties.

Topics•Medical imaging (image analysis by detection, segmentation, registration,
classification of pathological patterns, …)•

Medical signal and data processing (analysis of biosignals, automated systems for
detection of abnormal biomedical signals, detection of relevant biomedical patterns,

Special Session Chair
Ke Tang · ketang@ustc.edu.chnIEEE Conference on Evolutionary Computation
Donostia – San Sebastián, June 8-5
www.cec2017.org · info@cec2017.org

SPECIALSESSIONS

multi-scale signal processing, …)•Clinical diagnosis and therapy (knowledge discovery of relevant diagnostic
parameters, data mining to discover new information, processing of large volumes ofheterogeneous medical data, classification, clustering, regression models in
diagnosing diseases, earlier diagnosis of disease, disease prediction, prediction of how
diseases propagate, …)•Modelling and simulation of medical processes (modelling of medical processes toavoid mistakes or to systematically improve decision making and practice, error,
vulnerability, and inefficiencies detection, simulation of multi-agent concurrent
activities, …)•

Decision support and therapy (clinical decision support systems, automatic clinicaldiagnosis, treatment schedule, therapy planning, …)•

Evolutionary algorithms for chronic disease management (disease measure
estimates, identification of symptoms, …)•

Personalization of knowledge, care and devices (mining models of the patient,personalized clinical diagnosis, adaptation of medical devices to individual patients, …)•Healthcare modeling and healthcare simulation (physicians/patient support systems,population modelling systems, …)•Sanitary systems, ehealth, mhealth, sensors (e-solutions for clinical systems, wearable
devices, body sensors, multi-sensor data fusion, …)

2/2