Smart health advancement is making it possible to monitor and control the healthcare information of the individuals by developing health management models. The data generated by different sensors in the smart devices allows them to benefit in various fields but the diverse nature of medical data also makes it challenging to process those 'Big Data' Traditional algorithms do not offer flexibility to handle such large volumes of diverse data and that creates a need for proper mechanisms for data processing to be able to keep up with the response requirements as well as the data reliability. Big data analytics is the process of examining these large data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.

BIGDATA4HEALTH, organized in conjunction with IEEE CHASE 2016 , focuses on bringing together researchers and practitioners in mobile computing, biomedical and machine learning to showcase the progress, algorithms, and applications of analyzing and extracting knowledge from large-scale datasets for smart and connected healthcare.

We cordially invite you to submit unpublished manuscripts to BIGDATA4HEALTH, whose technical topics are available in the CFP. All accepted papers will be published by IEEE and indexed by IEEExplore. A select number of distinguished papers, after further major revisions, will also be considered for publication in special issues of IEEE Access (approved) and Journal of Medical Systems (under processing).