An Efficient Approach Towards the Generation and Analysis of Interoperable Clinical Data in a Knowledge Graph

Knowledge graphs have been shown to play an important role in recent knowledge mining and discovery, for example in the field of life sciences or bioinformatics. Contextual information is widely used for NLP and knowledge discovery in life sciences since it highly influences the exact meaning of natural language and also queries for data. The contributions of this paper are (1) an efficient approach towards interoperable data, (2) a runtime analysis of 14 real world use cases represented by graph queries and (3) a unique view on clinical data and its application combining methods of algorithmic optimisation, graph theory and data science.

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1. Track 1: Artificial Intelligence in Applications

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2. Session: 15th International Symposium Advances in Artificial Intelligence and Applications