Decoding Depression

Information technology could improve prevention, treatment of depression via data mining

(RxWiki News) Information technology and data mining could bring the power of computing to the development of depression treatments.

Maja Hadzic, Fedja Hadzic and Tharam Dillon of the Digital Ecosystems and Business Intelligence Institute, at Curtin University of Technology, in Perth, Australia, have developed a system that melds three different kinds of patient data with the help of mental health therapists and their interaction with the patients. Much like modern tree-mining techniques, the data-mining system highlights patterns that can be seen in the onset, treatment and management of depression. These patterns will improve understanding of the disease (which often precedes chronic conditions like high blood pressure and diabetes) and give practitioners new insights into prevention and treatment.

"Usually, an epidemic, such as a swine flu epidemic, has a pathogen associated with it. But, there is no pathogen involved with the depression epidemic," said the researchers.

Depression -- one of the major health problems now facing society -- stands to become the world's leading cause of disability by 2020, according to the World Health Organization (WHO). The disease is believed to be caused by a combination of biological, psychological and social factors. An estimated 19 million Americans currently live with major depression. Symptoms include a persistent feeling of sadness or hopelessness, lasting longer than two weeks and interfering with daily life. Difficulty concentrating, fatigue and weight loss or gain are also possible symptoms.  

Utilizing the research team's data-mining information technology, "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 while developing more effective treatment approaches," according to researchers.

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Review Date: 
December 5, 2010