Data Science in Medicine and Healthcare is a workshop with IEEE BigData 2020, Dec. 10-13, 2020 @ Atlanta, USA.
Due to the COVID-19 situation, the meeting is now taking place virtually.
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 big 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 in 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 include, but are not limited to (not in order of preference):
Important Dates:
Submission:
Please submit a full length paper (up to 10 page IEEE 2-column format) through the online submission system here. Please follow IEEE conference paper format.
Program Chairs:
Xiong Liu, Novartis, USA, [email protected]
Program Committee Members:
Peng Xia, Facebook, USA
Xiang Ji, Facebook, USA
Shinan Zhang, PwC AI, USA
Jason Anderson, Eli Lilly and Company, USA
Chunhui Hou, South University of Science and Technology of China
Zichen Wang, Icahn School of Medicine at Mount Sinai
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 include, but are not limited to (not in order of preference):
- Big data management
- Ontology and meta-data design
- Natural language processing and text mining
- Machine learning and deep learning
- Biological network analysis
- Gene-disease relationships
- Drug target identification and validation
- Quantitative structure-activity relationships (QSARs)
- Toxicity analysis and prediction
- Biomarker discovery
- Clinical trials analysis
- Real World Evidence (RWE)
- Electronic health records (EHR) mining
- Patient safety and outcomes
- Analysis and visualization of biological and clinical data
- Nanoinformatics and nanomedicine
- Infrastructure (frameworks/software/tools/resources) for health applications
Important Dates:
- Oct 23, 2020: Due date for full workshop papers submission
- Nov 11, 2020: Notification of paper acceptance to authors
- Nov 20, 2020 (firm date): Camera-ready of accepted papers
- Dec 10-13, 2020: Workshops
Submission:
Please submit a full length paper (up to 10 page IEEE 2-column format) through the online submission system here. Please follow IEEE conference paper format.
Program Chairs:
Xiong Liu, Novartis, USA, [email protected]
Program Committee Members:
Peng Xia, Facebook, USA
Xiang Ji, Facebook, USA
Shinan Zhang, PwC AI, USA
Jason Anderson, Eli Lilly and Company, USA
Chunhui Hou, South University of Science and Technology of China
Zichen Wang, Icahn School of Medicine at Mount Sinai
