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Diabetes Research Using New Data Models Makes Fresh Research Connections


The emergence of Big Data and other advances in data science approaches and tools are providing medical researchers with the opportunity for previously unobtainable insight – insights that have the potential to improve all our lives.

By its very nature, medical data is highly heterogeneous, and so it can be a real challenge to model. And what has also been realised is that it’s the relationships in data that we want to explore and uncover.

Graph database technology has appeared as a viable and powerful alternative here. One prominent convert to the approach Watch Pages is the German Centre for Diabetes Research, the DZD (Das Deutsche Zentrum für Diabetesforschung e.V.), which is planning to use graph software in combination with techniques such as artificial intelligence (AI) to make connections that no-one else is doing.

It’s not just graph software that is being employed. AI techniques like machine learning will play a key role going forward, says DZD, with a particular area of interest being building a system able to ‘read’ scientific texts and integrate them into the database ready for analysis. “Technology makes it easier to view medical issues from different perspectives and across indications,” Dr Jarasch points out. “This also makes it possible to identify correlations between various common diseases.”


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