Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data

Big Data in medical fields, such as hospital informatization construction, the progress of treatments, and the extensive use of high-throughput equipment, have caused a geometric growth of attentions. It has been desirable to improve the efficiency, accuracy and quality of medical data processing (Jee and Kim, 2013). The sources of health data include clinical medical treatments, pharmaceutical companies, medical research, medical assistance application, and more. Existing datasets bring in important medical and health information for research topics, such as understanding of the human genetic and disease systems (Joyce and Palsson, 2006), medical and biological imaging (Reiner, 2011); and classification and prediction in medical engineering (Kusiak et al., 2000).
Source: Computerized Medical Imaging and Graphics - Category: Radiology Authors: Source Type: research