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Text-Mined Knowledge Graphs — Beyond Text Mining

Text is the medium used to store the tremendous wealth of scientific knowledge regarding the world we live in. However, with its ever-increasing magnitude and throughput, analyzing this unstructured data has become an impossibly tedious task. This has led to the rise of Text Mining and Natural Language Processing (NLP) techniques and tools as the go-to for examining and processing large amounts of natural text data.

Text-Mining is the automatic extraction of structured semantic information from unstructured machine-readable text. The identification and further analysis of these explicit concepts and relationships help in discovering multiple insights contained in text in a scalable and efficient way.

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How to Use a Knowledge Graph for Precision Medicine

One of the biggest challenges in our current state of medicine is to provide relevant, personalized, and precise diagnoses and treatments. Rather than treating all patients the same, the goal is to fully take into account a person's demographics and genetic profile while treating or diagnosing them.

In a nutshell, the current problem is that a large number of drugs and treatments prescribed to patients do not treat the individual patient, but the generic disease. This is something doctors are well aware of — not all treatments affect every patient in the same way. Yet for decades, the strategy of trial and error is still being used to a large extent to treat and diagnose. Not the most reassuring of thoughts.