A special section on computational systems for medical and health informatics

• Main Authors: Li, Xiaoli, Kwoh, Chee Keong, Zheng, Jie, Cho, Sung-Bae
• Other Authors: School of Computer Engineering
• Format: Article
• Language: English
• Published: 2015
• Subjects: DRNTU::Science::Medicine::Tissue engineering; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
• Online Access: https://hdl.handle.net/10356/96358; http://hdl.handle.net/10220/38500
• Institution: Nanyang Technological University

The 5th International Conference on Computational SystemsBiology and Bioinformatics (CSBio2014) was hosted at Nanyang Technological University from 10th to 12th November 2014, and was jointly organised by Nanyang Technological University, King Mongkut’s University of Technology Thonburi, National University of Singapore, and Agency for Science, Technology and Research (A∗STAR). The CSBio conference brought together researchers and practitioners to exchange ideas and stimulate research collaborations in response to rapid advances in the generation of high-throughput “omics” data (such as deep sequencing) and clinical data (e.g., biomedical images, and electronic health records). To extract novel biological knowledge from the heterogeneous data sources, and translate it into useful biological and clinical applications to benefit the society (e.g., better medicine and healthcare), novel computational techniques, tools, and domain knowledge and insights are needed. We kept to the tradition of carefully selecting a handful of high-quality papers to recommend for journal publications. This year, we teamed up with the promising Journal of Medical Imaging and Health Informatics (JMIHI) to publish our selected papers. Particularly, we have selected six (6) papers for JMIHI. In the era of big data challenges, as the availability of biological information becomes ever larger and more complex for Medical and Health informatics, more computational tools are needed to sort through the data.