Sleep conditions such as sleep apnea are well understood, but a far more common disorder, insomnia, is not as well understood. Therefore, tailored treatments have not been developed. Australia’s Woolcock Institute of Medical Research, part of the University of Sydney, thinks data science is the key to learning more about insomnia and producing better treatments.
Oracle Autonomous Data Warehouse is easy to access, easy to upload data—no matter what kind of format, structured or unstructured—then visualize the data and manage machine learning.
Data Scientist, Woolcock Institute of Medical Research
It usually takes Woolcock researchers weeks and sometimes months to process research data. Now, with that data integrated in Oracle Autonomous Data Warehouse, researchers can visualize it in different ways, come up with new ideas, and then literally click buttons to manage the machine learning and explore different models, yielding answers almost immediately.
A main goal of the sleep team’s data analysis is to acquire a better understanding of anomalous patterns in insomnia, such as patients who report insomnia symptoms though their brain sleep patterns appear normal, while other patients who report similar symptoms have brain sleep pattern changes that show deficits in “slow-wave” activity.
Oracle Autonomous Data Warehouse helps the sleep researchers piece together those variables. “The system is very friendly, even for people who have no idea about the programming,” says Dr. Tancy Kao, a data scientist at Woolcock Institute of Medical Research.