The use of data mining can help researchers identify biomarkers for Alzheimer's disease, according to a study published in the Journal of Translational Medicine, Clinical Innovation & Technology reports.
How Researchers Mined Data
For the study, researchers from King's College London in the United Kingdom developed statements about the appearance of blood biomarkers.
They then used textual and linguistic analyses to create a computer code that they applied to public databases.
Based on the statements about the appearance of blood biomarkers, the computer code identified 25 potential biomarkers for Alzheimer's disease.
The researchers then validated the 25 biomarkers, finding that some of them previously had been identified as potential Alzheimer's biomarkers (Clinical Innovation & Technology, 11/8).
Simon Lovestone -- lead author of the study and a professor of old age psychiatry at the King's College London's Institute of Psychiatry -- in a statement said the study demonstrates the effectiveness of data mining. He said that researchers "will take this [technique] forward in our hunt for Alzheimer's biomarkers."
Lovestone added that the same approach could be used to study other conditions, such as cancer or diabetes (Bowman, FierceHealthIT, 11/8).