Please login first
SUIWML01: International Workshop on Machine Learning in Biomedicine, Soochow, China, 2016
1 , 1 , 2 , * 2
1  School of Computer Science and Technology, Soochow University, Soochow, China
2  Center for Systems Biology, Soochow University, Suzhou, Jiangsu, China


This workshop is focus on Machine Learning. Machine learning is the most growing branch of computer science, driven by the ongoing explosion in the availability of data. Machine learning evolved from artificial intelligence and deals with many different problems and aspects to solve various tasks, including knowledge discovery, data mining, decision support and etc. A grand challenge is to discover relevant structural patterns and/or temporal patterns in complex data, which are often hidden and not accessible to the human expert.

Biomedicine is a branch of medical science that applies biological and other natural-science principles to clinical practice. The branch especially applies to biology and physiology, which has been the dominant health system for more than a century. Nowadays, the dramatic growth of medical and biological data has created an unprecedented opportunity for machine learning in the pattern recognition and machine learning community. Many medical and biological problems involve challenging approaches to pattern discovery and learning.

This workshop aims at highlighting the on-going research both the advancement of machine learning technologies and the improvements of biomedicine, and trying to bringing together researchers from the related fields to foster discussion and elicit open problems on machine learning and its applications in biomedicine. The workshop will consist of invited talks, contributed presentations, and posters. We plan to include an opening tutorial and an overview of the state-of-the-art techniques. Invited talks will be given by leading experts from both machine learning and biomedicine. We hope this workshop will not only provide an opportunity for international researchers to exchange ideas and present the latest promising work, but also create a platform to discuss and identify important future topics and directions in related fields for further research and collaboration.

Keywords: Machine Learning; Medical informatics; Bioinformatics; Cheminformatics