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Introduction

This workshop is on medical data mining to improve healthcare. It aims to provide a forum for data miners, informaticians, data scientists, and clinical researchers to share their latest investigations in applying data mining techniques to healthcare data residing in electronic health records (EHR). The increasing availability of large and complex medical data sets to the research community triggers the need to develop more advanced and sophisticated big data analytical techniques to exploit and manage these big data. The broader context of the workshop comprehends artificial intelligence, information retrieval, machine learning, 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. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR) and will be posted on the workshop website. We plan to organize a journal special issue and invite extended versions of the accepted papers for that. 

Call for paper

Important date

2017-05-31
Draft paper submission deadline
2017-06-16
Draft paper acceptance notification

Submission Topics

  • Clustering big data in EHRs to identify patients with similar disease/symptom/treatment

  • Building predictive models for diseases from big data in the EHR.

  • Generating lexicons/vocabularies of diseases of interest using deep learning algorithms

  • Establishing patients’ cohorts with targeted diseases using information retrieval techniques

  • Discovering risk factors of diseases using natural language processing methods

  • Longitudinal analysis of temporal data in EHRs

  • EHR summarization

  • Topic modeling / detection in large amounts of clinical text data

  • Integrating structured (tabulated) and unstructured (text narratives) data in the EHR.

  • 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

  • Pharmacogenomics data mining

  • Data preprocessing and cleansing to deal with noise and missing data in the EHR.

  • Developing decision support approaches (especially with uncertain data) in the EHR

  • Multi-view learning of the heterogeneous EHR 

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Important Date
  • Aug 14

    2017

    Conference Date

  • May 31 2017

    Draft paper submission deadline

  • Jun 16 2017

    Draft Paper Acceptance Notification

  • Aug 14 2017

    Registration deadline

Sponsored By
美国计算机学会
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