IT Can Be Used To Prevent and Treat Depression

by VR Sreeraman on  December 6, 2010 at 12:28 PM News on IT in Healthcare   - G J E 4
Information technology and data mining techniques can be used to improve the diagnosis and treatment of depression, suggests a new study.
 IT Can Be Used To Prevent and Treat Depression
IT Can Be Used To Prevent and Treat Depression

Depression often precedes and may cause, directly or indirectly, many chronic conditions such as high blood pressure and diabetes. Using information technology could bring to bear the power of computing in early diagnosis and the development of treatments.

Maja Hadzic, Fedja Hadzic and Tharam Dillon of the Curtin University of Technology have developed a system that integrates three different kinds of patient data as well as the data describing mental health of therapists and their interaction with the patients.

This system can be data-mined using standard techniques as well as modern tree-mining techniques so that patterns can be seen in the onset, treatment and management of depression.

"The data describing patients' activities, bodily functions and feelings as well as the data describing mental health of therapists will be collected and collectively mined to reveal interesting patterns," explained the team.

The patterns that emerge from data mining this information will not only improve understanding of the disease, but could give practitioners new insights into prevention and treatment.

Their approach balances the fact that no two cases of depression are the same as all patients are individuals and all are different whereas healthcare practitioners do observe similarities in behaviour and response to treatment between different patients.

"Patients will be able to receive highly personalized treatments, the therapists will be assisted in making evidence-based decisions, and the scientist will be able to pursue new knowledge revealing true causes of depression whilst developing more effective treatment approaches," concluded the team.

The findings were published in the International Journal of Functional Informatics and Personalised Medicine.

Source: ANI

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