Author: Andreas Antoniades (PhD student)
The flagship conference for neural networks, 2016 International Joint Conference on Neural Networks (IJCNN 2016), was held as part of the IEEE World Congress on Computational Intelligence (WCCI 2016) in the beautiful city of Vancouver, British Columbia, Canada. The conference took place between the 24th to 29th July. The objective of this bi-annual congress is to bring together the latest advancements in Computational Intelligence.
The conference was a great opportunity for me to present and promote my work, as well as meet some of the pioneers in the area of machine learning. Throughout the week, I was able to benefit from a number of parallel sessions and discuss possible collaborations with academics from different institutions and different research areas.
My presented work revolved around the concept of feature selection for cancer in children. Given a dataset of patient records, it is important to understand which genes are most important for the detection and treatment of Neuroblastoma, Rhabdomyosarcoma, non-Hodgkin lymphoma and the Ewing family of tumors. Clinicians often have to consider thousands of genes in order to correctly diagnose and treat a patient. The proposed algorithm utilised the latest advancements in Autoencoders to select the most important genes in an automatic manner, substantially reducing diagnostic waiting times.