Biomedical ontologies and controlled terminologies provide structured domain knowledge to a variety of health information systems. The rich biomedical knowledge and information encoded in ontologies have been widely used in various learning tasks such as natural language processing (NLP), data mining, machine learning, semantic annotation, and automated reasoning. On the other hand, methods in NLP and machine learning have also advanced the curation of biomedical ontologies from mainly manual construction to (semi-)automated construction at scale.
Moreover, the increasing amount of health-related data poses unprecedented opportunities for mining previously unknown knowledge with semantics-powered data mining and analytical methods. However, due to the heterogeneity of different data sources ranging from electronic health records (EHRs) to environmental exposures, from social determinants of health to social media, it is challenging to exploit and integrate multiple sources to solve real-world problems. Biomedical ontologies and semantics-powered analytical methods are promising solutions.
We are inviting original research submissions as well as work-in-progress to the 6th International Workshop on Semantics-Powered Health Data Analytics (SEPDA 2021).
Topics of interest include but not limited to:
We are inviting full paper submissions (up to 9 pages) as well as work-in-progress (up to 4 pages) to the 6th International Workshop on Semantics-Powered Health Data Analytics (SEPDA 2021).
Submissions must be in English formatted in the style of KR 2021. Submissions are not anonymous (i.e., reviewing will be single-blind) and have to be formatted using the following style files: KR21_authors_kit.zip
To submit the paper to SEPDA 2021, please visit this link: https://easychair.org/my/conference?conf=sepda2021#
SEPDA 2021 proceedings will be published in CEUR Workshop Proceedings (http://ceur-ws.org/). Authors of the accepted presentations will be invited to publish an extended paper in a peer-reviewed journal in biomedical and health informatics or semantic web.