A new analytical tool will be used by the US Army to identify soldiers who are at high risk of committing suicide.

Over a six-year period, 40,820 US soldiers were hospitalized for psychiatric problems and 68 of these soldier committed suicide within a year, according to reports.

For the research, the researchers designed an algorithm program with an aim to identify which US Army patient is at risk of committing suicide.

According to the algorithm, there were 947 at risk and the 68 people committed suicide. Ronald Kessler, a sociologist and suicide expert from Harvard University said that there is possibility that statistical model can be used to target suicide prevention efforts.

He helped in creating the algorithm program that will help to identify soldiers at risk of committing suicides. Between 2004 and 2009, it was noted that the Army had an annual suicide rate of 18.5 in every 100,000 soldiers.

In order to create the algorithm, the researchers combined 421 variables from each soldier strain from 38 military data systems.

The researchers identified about two dozen factors that proved to be most significant in identifying who is at risk through 'machine learning'.

According to Dr. Eric Schoomaker, who served as surgeon general of the Army, there had been suicide prevention programs started by the Army.

After observing the result of the research, Schoomaker would ask the Army to concentrate on soldiers at maximum risk.

Soldiers passed screening tests and fitness standards tests, which show that they are psychologically healthier, but reports signify that Army suicide rate is nearly similar to the rate of civilians committing suicide.