DMBIH 2018 - Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare

The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare aims to provide a forum for data miners, informacists, data scientists, and clinical researchers to share their latest investigations in applying data mining techniques to biomedical and healthcare data. The increasing availability of large and complex data sets to the research community, triggers the need to develop more advanced and sophisticated data analytical techniques to exploit and manage these big data. The broader context of the workshop comprehends artificial intelligence, information retrieval, machine learning, and knowledge extraction methods using biomedical image analysis and natural language processing.
Submissions are invited to address the need for developing new methods to mine, summarize and integrate the huge volume and diverse modalities of the structured and unstructured biomedical and healthcare data that can potentially lead to significant advances in the field.
Topics
Topics of interest include, but are not limited to:
Classifying and clustering big data in electronic health records (EHRs)
Classifying and clustering temporal data in EHRs and biomedical data in high dimensional spaces
Application of deep learning methods to clinical data
Topic modeling / detection in large amounts of clinical textual data
Data preprocessing and cleansing to deal with noise and missing data in large biomedical or population health data sets
Algorithms to speed up the analysis of big biomedical data
Novel visualization techniques to facilitate the query and analysis of clinical data
Statistics and probability in large-scale data mining
Evidence-based medicine
Developing efficient computational algorithms for mining/analyzing big EHR data
Novel visualization techniques to facilitate the query and analysis of clinical data
Statistics and probability in large-scale EHR data mining
Medical image data mining
HIPAA compliance data mining
Pharmacogenomics data mining
Biological markers detection
Biological and clinical data analysis and integration for translational research
Computational genetics, genomics and proteomics