Friday November 22, 2019

Game “Pokemon Go” to have added 2.83 million years of Life Expectancy by getting people off Couch to Hunt for Virtual Monster

When totalled, researchers said cumulatively, the roughly 25 million Pokemon Go-playing Americans took 144 billion more steps or the equivalent of 143 round trips to the moon

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FILE - A Pokemon Go player consults his phone while walking through the Boston Common outside the Massachusetts Statehouse. The game has introduced players to some aspects of history they otherwise might have missed. VOA

Forget fitness trackers and fitness apps.

Researchers say the augmented reality game Pokemon Go could have added 2.83 million years of life expectancy by simply getting people off the couch to hunt for virtual monsters.

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The study was done by Microsoft Research and found that Pokemon Go players, on average, increased the number of steps they took by 26 percent, with the most sedentary benefiting the most. Looked at another way, that’s 194 more steps per day taken, or roughly 160 meters.

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When totalled, researchers said cumulatively, the roughly 25 million Pokemon Go-playing Americans took 144 billion more steps or the equivalent of 143 round trips to the moon.

Activity increases were seen among genders, ages, weight and general levels of health.

The researchers say that since activity lowers mortality, all the extra activity from Pokemon Go could mean 2.83 million more years of life expectancy. Players who take 1,000 steps per day could lengthen their lives by 41.4 days.

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The one downside of the study is that interest in the game appeared to have peaked in the summer. Less interest and colder weather could reduce the number of players sharply.

The study was posted in the Cornell University Library. (VOA)

Next Story

This AI Tool Can Predict Mortality Of Heart Failure Patients

Researchers develop a tool that can predict mortality of heart failure patients

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This artificial intelligence (AI) tool can predict life expectancy in heart failure patients. Pixabay

Researchers have developed an artificial intelligence (AI) tool to predict life expectancy in heart failure patients.

The machine learning algorithm based on de-identified electronic health, records data of 5,822 hospitalised or ambulatory patients with heart failure at UC San Diego Health in the US.

“We wanted to develop a tool that predicted life expectancy in heart failure patients, there are apps where algorithms are finding out all kinds of things, like products you want to purchase,” said Avi Yagil, Professor at University of California.

“We needed a similar tool to make medical decisions. Predicting mortality is important in patients with heart failure. Current strategies for predicting risk, however, are only modestly successful and can be subjective,” Yagil added.

From this model, a risk score was derived that determined low and high risk of death by identifying eight readily available variables collected for the majority of patients with heart failure:Diastolic blood pressure, Creatinine, Blood urea nitrogen, White blood cell count, Platelets, Albumin and Red blood cell distribution.

Yagil said the newly developed model was able to accurately predict life expectancy 88 per cent of the time and performed substantially better than other popular published models.

“This tool gives us insight, for example, on the probability that a given patient will die from heart failure in the next three months or a year,” said researcher Eric Adler.

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The mortality of a heart failure patient can be predicted. Pixabay

“This is incredibly valuable. It allows us to make informed decisions based on a proven methodology and not have to look into a crystal ball,” he added.

The tool was additionally tested using de-identified patient data from the University of California San Francisco and a data base derived from 11 European medical centers.

“It was successful in those cohorts as well,” said Yagil.

“Being able to repurpose our findings in independent populations is of utmost importance, thus validating our methodology and its results,” Yagil added.

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Researchers said the partnership between physicists and cardiologists was critical to developing a reliable tool and extensive knowledge and experiences from both sides proved synergetic.

The study was published in the European Journal of Heart Failure. (IANS)