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BBH 2013 : The first International Workshop on BigData in Bioinformatics and Health Care Informatics | |||||||||||
Link: http://www.ittc.ku.edu/~jhuan/BBH | |||||||||||
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Call For Papers | |||||||||||
The first International Workshop on BigData in Bioinformatics and Health Care Informatics (BBH’13) offers a premier forum of presenting big data concepts, infrastructure, and analytics tools for integrating data from heterogeneous multimedia sources and expediting research in a wide range of areas including computer science, computational science, biological, biomedical, pharmaceutical, nursing, clinical care, dentistry, and public health. We welcome submissions covering any aspects of big data in Bioinformatics and Health Informatics. Below we list a few examples. Bioinformatics and Biomedical Informatics Next generation sequencing data storage and analysis Large scale biological network construction and learning Population based bioinformatics Genome structural change detection Large-scale bio-image and medical-image analysis Big data in molecular simulation and protein structure prediction Big data in systems biology Big data in drug discovery, development, and post-market surveillance Big data in semantics and bio-text mining Healthcare System Security and Privacy for clinical data in big data infrastructures Health IT implementations and demonstrations Case Studies for Hadoop based healthcare analytics Benchmarking of big data infrastructure in healthcare Real time aspects of healthcare data infrastructure Novel data analysis algorithms that enable easy, rapid knowledge discovery from complex EMR Analytics for Visualizing and summarizing large patient data in EMR Novel algorithms and applications dealing with noisy, incomplete but large amounts of EMR data Integrating genomic data for improving human health Data science and modeling for health analytics Advances in new storage models for data variety (records, images, MRI, scans) for hospitals Big data challenges in Accountable Care settings Extracting meaning from multi-structured big data in realtime to improve outcome Combining information from Imaging (RIS, PACS), EHR, Labs, Genomics to give coherent diagnosis and treatment Leveraging social networks for data aggregation Smart visualizations for big data streams Big data and analytics from home monitoring devices Big data design patterns and anti-patterns Health Data Analysis How to co-register patient data acquired over several time-points in their life? What are the important metadata that need to be tracked over the longitudinal duration? What software platforms need to be developed for enabling easy access to the patient's medical and clinical history? How to handle gaps in history-taking? What is the current state-of-the-art in clinical decision support utilizing personalized longitudinal medical data and what is missing? |
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