Jun 10-13, 2019, Wellington, New Zealand
We proposed a special session on “Evolutionary Computation in Healthcare Industry” in IEEE Congress on Evolutionary Computation 2019 (CEC 2019). Please consider to contribute to and/or forward to the appropriate groups the following opportunity to publish original research articles in CEC 2019.
Call for Papers
Summary of the special session:
Worldwide, the healthcare industry would continue to thrive and grow, because diagnosis, treatment, disease prevention, medicine, and service affect the mortal rates and life quality of human beings. Two key issues of the modern healthcare industry are improving healthcare quality as well as reducing economic and human costs. The problems in the healthcare industry can be formulated as scheduling, planning, predicting, and optimization problems, where evolutionary computation methods can play an important role. Although evolutionary computation has been applied to scheduling and planning for trauma system and pharmaceutical manufacturing, other problems in the healthcare industry like decision making in computer-aided diagnosis and predicting for disease prevention have not properly formulated for evolutionary computation techniques, and many evolutionary computation techniques are not well-known to the healthcare community. This special session aims to promote the research on evolutionary computation methods for their application to the healthcare industry.
Scope and Topics:
The topics of this special session include but are not limited to the following topics:
• Evolutionary computation in resource allocation for hospital location planning, aeromedical retrieval system planning, etc.
• Application of evolutionary computation for job scheduling, such as ambulance scheduling, nurse scheduling, job scheduling in medical device and pharmaceutical manufacturing, etc.
• Multiple-criteria decision-making for computer-aided diagnosis using expert systems.
• Web self-diagnostic system with the application of information retrieval and recommendation system.
• Learning and optimization for vaccine selection and personalized/stratified medicine.
• Data-driven surrogate-assisted evolutionary algorithms in pharmaceutical manufacturing processes.
• Modeling and prediction in epidemic surveillance system for disease prevention.
• Route planning for disability robots.
-Paper submission: 7th January, 2019
-Notification to authors: 7th March, 2019
-Final submission: 31st March, 2019
-Early registration: 31st March, 2019
Handing Wang, Department of Computer Science, University of Surrey, UK
Rong Qu,School of Computer Science, University of Nottingham, UK
Yaochu Jin, Department of Computer Science, University of Surrey, UK