The recent advances in biomedicine and health sciences have led to a vast increase in the amount of structured (e.g., diagnoses, medications, laboratory results) and unstructured (e.g., scientific articles, patents, conference abstracts, health forums) data. This provides an excellent opportunity to extract useful information from these data via data mining/machine learning. However, transforming data to action gives rise to the key challenge in informatics and data science: to develop innovative methods and systems for acquisition, curation, management, processing, visualization, and interoperation of large amounts of data involved with health.
The goal of this workshop is to provide a forum for scientists and engineers in the growing community of health data science to exchange ideas and discuss the latest research developments. Papers submitted to the workshop should address the novelty and significance of the methodologies and use cases. The implications of the results and the potentially transformative nature of the proposed work should also be discussed to demonstrate how data science can effectively impact health.
Research topics of the workshop include, but are not limited to (not in order of preference):
Important Dates
Program Chairs or co-chairs:
Program Committee Members:
The goal of this workshop is to provide a forum for scientists and engineers in the growing community of health data science to exchange ideas and discuss the latest research developments. Papers submitted to the workshop should address the novelty and significance of the methodologies and use cases. The implications of the results and the potentially transformative nature of the proposed work should also be discussed to demonstrate how data science can effectively impact health.
Research topics of the workshop include, but are not limited to (not in order of preference):
- Ontology and meta-data design
- Natural language processing and text mining
- Machine learning and modeling
- Gene-disease relationship mining
- Biological network analysis
- Drug target identification and validation
- Computational biomarker discovery
- Electronic health records (EHR) mining
- Analysis and visualization of biological and clinical data
- Quantitative structure-activity relationships (QSARs)
- Toxicity analysis and prediction
- Nanoinformatics and nanomedicine
- Infrastructure (frameworks/software/tools/resources) for health applications
Important Dates
- Sep 20, 2017: Due date for full workshop papers submission
- Oct 10, 2017: Notification of paper acceptance to authors
- Oct 25, 2017: Camera-ready of accepted papers
- Nov 13, 2017: Workshops
Program Chairs or co-chairs:
- Xiong Liu, Eli Lilly and Company, USA, [email protected]
Program Committee Members:
- Rong Liu, Equifax, USA
- Peng Xia, Microsoft, USA
- Xiang Ji, Bloomberg, USA
- Yanping Huang, Google.com, USA
- Nan Wang, Linkedin.com, USA
- Jason Anderson, Eli Lilly and Company, USA
- Malika Mahoui, Eli Lilly and Company, USA
- Stuart Morton, Eli Lilly and Company, USA
- Chunhui Hou, South University of Science and Technology of China
- Zichen Wang, Icahn School of Medicine at Mount Sinai