Special Session on Evolutionary Computation in Healthcare and Biomedical Data



Special Session organizers:

1. Dr. Mukesh Prasad, University of Technology Sydney, Australia

2. Associate Professor Paul J. Kennedy, University of Technology Sydney, Australia,

3. Dr. Manoranjan Mohanty, University of Auckland, New Zealand

Aims and Scope:

Healthcare and biomedical sciences have become data-intensive fields, with a strong need for sophisticated data mining methods to extract the knowledge from the available information. For example, data analysis methods are applied on biomedical datasets, namely DNA microarray data or Next Gen sequencing data to predict treatment outcomes of paediatric Acute Lymphoblastic Leukaemia patients. Moreover, clustering methods are routinely used to investigate the interpretation of the correlated genes associated with cellular and biological function.

Biomedical data contains several challenges in data analysis, including high dimensionality, class imbalance and low numbers of samples. Although the current research in this field has shown promising results, several research issues need to be explored as follows. There is a need to explore feature selection methods to select stable sets of genes to improve predictive performance along with interpretation. There is also a need to explore big data in biomedical and healthcare research. An increasing flood of data characterises human health care and biomedical research. Healthcare data are available in different formats, including numeric, textual reports, signals and images, and the data are available from different sources. An interesting aspect is to integrate different data sources in the data analysis process which requires exploiting the existing domain knowledge from available sources. The data sources can be ontologies, annotation repositories, and domain experts’ reports.

This special session aims to bring together the current research progress (from both academia and industry) on data analysis for biomedical and healthcare applications. It will attract healthcare practitioners who have access to interesting sources of data but lack the expertise in using the data mining effectively. Special attention will be devoted to handle feature selection, class imbalance, and data fusion in biomedical and healthcare applications.


The main topics of this special session include, but are not limited to, the following:

1. Information fusion and knowledge transfer in biomedical and healthcare applications.

2. Data Analysis of the biomedical data including genomics.

3. Text mining for medical reports.

4. Statistical analysis and characterization of biomedical data.

5. Machine Learning Methods Applied to Medicine

6. Large Datasets and Big Data Analytics on biomedical and healthcare applications.

7. Information Retrieval of Medical Images

8. Single cell sequencing analysis

9. Medical imaging and genomics

Paper Submission:

The papers should be submitted through IEEE CEC’s submission central. After logging into the submission system, you need to choose Special Session on “Evolutionary Computation in Healthcare and Biomedical Data”.

Important Dates:

Paper submission due: Jan. 7, 2019

Notification of acceptance: Mar. 7, 2019

Author registration deadline: Mar. 31, 2019

Camera-ready deadline: Mar. 31, 2019

Information about IEEE CEC 2019: http://cec2019.org/#

We look forward to receiving your high-quality submissions.