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Depressed teenagers at greater heart disease risk

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New York: Major depressive disorder and bipolar disorder predispose youth to early cardiovascular disease, the American Heart Association (AHA) has said. 

The AHA statement is based on a group of recent studies including those that reported cardiovascular events such as heart attacks and deaths among young people.

For example, a 2011 population study of over 7,000 young adults in the US under the age of 30, found that depression or an attempted suicide was the No.1 risk factor for heart disease death caused by narrowed/clogged arteries in young women, and the No.4 risk factor in young men.

“Youth with mood disorders are not yet widely recognized as a group at increased risk for excessive and early heart disease. We hope these guidelines will spur action from patients, families and healthcare providers to reduce the risk of cardiovascular disease among these youth,” said Benjamin I. Goldstein, lead author of the statement.

Since cardiovascular disease may begin early in life, the authors want to increase awareness and recognition of mood disorders among young people as moderate-risk conditions for early cardiovascular disease.

After systematically analyzing published research, the authors found that teens with major depression or bipolar disorder are more likely than other teens to have several cardiovascular disease risk factors including high blood pressure, high cholesterol, obesity and type-2 diabetes.

“Mood disorders are often lifelong conditions, and managing cardiovascular risk early and assertively is tremendously important if we are to be successful in ensuring that the next generation of youth has better cardiovascular outcomes,” Goldstein, a child-adolescent psychiatrist, said.

The findings were published in Circulation, a journal of the American Heart Association.

(IANS)

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Novel AI Tool to Detect Depression Via Sound of Your Voice

Such a tool could prove useful to support work with care providers or to help individuals reflect on their own moods over time

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Depression is a major issue affecting millions of people, especially the teenagers. Pixabay

India — the sixth most depressed country in the world — has an estimated 56 million people suffering from depression and 38 million from anxiety disorders, according to a recent report by the World Health Organisation (WHO).

To help identify depression early, scientists have now enhanced a technology that uses Artificial Intelligence (AI) to sift through sound of your voice to gauge whether you are depressed or not.

Computing science researchers from University of Alberta in Canada have improved technology for identifying depression through vocal cues.

The study, conducted by Mashrura Tasnim and Professor Eleni Stroulia, builds on past research that suggests that the timbre of our voice contains information about our mood.

Using standard benchmark data sets, Tasnim and Stroulia developed a methodology that combines several Machine Learning (ML) algorithms to recognize depression more accurately using acoustic cues.

A realistic scenario is to have people use an app that will collect voice samples as they speak naturally.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

“The app, running on the user’s phone, will recognize and track indicators of mood, such as depression, over time. Much like you have a step counter on your phone, you could have a depression indicator based on your voice as you use the phone,” said Stroulia.

Depression is ranked by WHO as the single largest contributor to global disability. It is also the major contributor to suicide deaths.

The ultimate goal, said researchers, is to develop meaningful applications from this technology.

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Such a tool could prove useful to support work with care providers or to help individuals reflect on their own moods over time.

“This work, developing more accurate detection in standard benchmark data sets, is the first step,” added Stroulia while presenting the paper at the Canadian Conference on Artificial Intelligence recently. (IANS)