IEEE CIS Task Force on
Intelligence Systems for Health
Motivation
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. Although many clinical researches have been dedicated to the healthcare industry, the gap between the increasing health need from human beings and the current development of this area is still challenging to be narrowed down.
The problems in the healthcare industry can be formulated as scheduling, planning, predicting, and optimization problems, where artificial intelligence methods can play an important role. For example, reasonable scheduling and planning for trauma system and pharmaceutical manufacturing can save the resource costs; computer-aided diagnosis and web self-diagnostic system can alleviate doctors’ workload; learning and optimization from data can shorten the period of pharmaceutical research; robots can enhance the life quality of disabled people.
Intelligence systems with novel artificial intelligence techniques have been highly developed and widely applied to various industry areas in the last decade, which brings new opportunities to the healthcare industry. However, the communities of healthcare and artificial intelligence are not tightly connected. Many problems in the healthcare industries are even not properly formulated for artificial intelligence techniques, and many artificial intelligence techniques are not well-known to the healthcare community.
The main goal of this task force is to promote the research on artificial and computational intelligence methods for their application to the healthcare industry.
Scope
The scope of this task force includes, but is not limited to:
Resource allocation for hospital location planning and aeromedical retrieval system planning.
Job scheduling for ambulance scheduling, nurse scheduling, and job scheduling in medical device and pharmaceutical manufacturing.
Computer-aided diagnosis using expert systems, decision making system, machine learning and deep learning.
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 optimization in pharmaceutical manufacturing processes.
Modeling and prediction in epidemic surveillance system for disease prevention.
Human-computer interaction and semantic interoperability for disability robots.
Activities
Current
Special Session on "Evolutionary Computation in Healthcare Industry" at CEC 2024
Special Session on "Large-scale Multi-objective Optimization" at CEC 2024
Competition on "Super Large-scale Multiobjective Optimization for Status Assessment of Measuring Equipment" at CEC 2024
Past
Competition on "Large-scale Continuous Optimization for Non-contact Measurement" at CEC 2023
Special Session on "Evolutionary Computation in Healthcare Industry" at CEC 2023
Special Session on "Large-scale Multi-objective Optimization in Emerging Applications" at CEC 2023
IEEE Symposium on “ Model-Based Evolutionary Algorithms” at IEEE SSCI 2022
Special Session on "Evolutionary Computation in Healthcare Industry" at WCCI 2022
Special Session on “Large-scale Multi- and Many-objective Optimization and its Applications” at CEC 2021
Special Issue on "Emerging Topics in Evolutionary Multiobjective Optimization" at Complex & Intelligence System
Special Session on “Evolutionary Computation in Healthcare Industry” at CEC 2020
Special Session on “Evolutionary Computation in Healthcare Industry” at CEC 2019
Symposium on “Computational Intelligence in Healthcare and E-Health” at SSCI 2018
Special Session on “Evolutionary Computation in Healthcare Industry” at WCCI 2018
Chairs
Cheng He (Chair), Huazhong University of Science and Technology, China
Rong Qu (Vice Chair), University of Nottingham, UK
Zhichao Lu (Vice Chair), City University of Hong Kong, Hong Kong
Members
Amir Hussain, Edinburgh Napier University, UK
Handing Wang, Xidian University, China
Lilian Tang, University of Surrey, UK
Shan Tan, Huazhong University of Science and Technology, China
Stephen Smith, University of York, UK
Shan He, University of Birmingham, UK
Sanaz Mostaghim, Otto von Guericke University of Magdeburg, Germany
Mengjie Zhang, Victoria University of Wellington, New Zealand
Emma Laing, University of Surrey, UK
Ross King, University of Manchester, UK
Zengguang Hou, Chinese Academy of Sciences, China
Casey Bennett, Centerstone Research Institute, US
Margaret Varga, University of Oxford, UK
Yaochu Jin, Westlake University, China
Narayan Venkataraman, Changi General Hospital, Singapore
Mufti Mahmud, Nottingham Trent University, UK