DMBIH 2017 - Data Mining in Biomedical Informatics and Healthcare (DMBIH) Workshop 2017
Topics/Call fo Papers
The Fifth 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
Clinical big data
Classifying and clustering in electronic health records (EHRs)
Classifying and clustering temporal data in EHRs and biomedical data
in high dimensional spaces
Topic modeling and/or detection in large amounts of clinical textual data
Longitudinal analysis of clinical notes and surveys and time series analysis
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
Medical image data mining
HIPAA compliance data mining
Pharmacogenomics data mining
Biological markers detection
Computer-aided detection and diagnosis
Biological and clinical data analysis and integration for translational research
Computational genetics, genomics and proteomics
Topics
Clinical big data
Classifying and clustering in electronic health records (EHRs)
Classifying and clustering temporal data in EHRs and biomedical data
in high dimensional spaces
Topic modeling and/or detection in large amounts of clinical textual data
Longitudinal analysis of clinical notes and surveys and time series analysis
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
Medical image data mining
HIPAA compliance data mining
Pharmacogenomics data mining
Biological markers detection
Computer-aided detection and diagnosis
Biological and clinical data analysis and integration for translational research
Computational genetics, genomics and proteomics
Other CFPs
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- 1ST WORKSHOP ON DATA MINING FOR AGING, REHABILITATION AND ASSISTED LIVING (ARIAL)
- HighStream’2017 High-Performance Data Stream Mining Workshop
- First IEEE International Workshop on HPC based Deep Learning
- 1st International Workshop on Data Science for Human Capital Management (DSHCM)
Last modified: 2017-05-13 11:38:10