• The research has been published in the journal Scientific Research.
• Search engine traces constitute an ever-growing data pool, which are now being exploited by scientists

LONDON, July 28, 2017: Today's good news comes from the field of medicine! Researchers at University of Warwick, UK in a path-breaking research propose that key words about symptoms and risk-factors of Type 2 diabetes, when entered into search engines or posted on social media, can provide accurate real-time information on how likely the disease is to multiply in specific areas and its primary conditions.

Type 2 diabetes is a lifestyle disease that can result due to factors like diet, exercise and family history of diabetes. However, it is difficult to detect, the procedure typically involving tests of blood, glucose, and urine along with the physical examination.

Scientists believe this effective monitoring of Type 2 Diabetes using Google searches will help public officials keep a track of the disease and curb its spread.

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Researchers looked at diabetes risk factors from two principal UK observation models that monitor the disease in those who're at risk of developing it, or those who already suffer – including gender, age, weight, body mass index (BMI), family history of diabetes and lifestyle choices (like smoking). They then analyzed Google Trends data from Central London, comparing weekly searched keywords relating to risk factors such as "how to quit smoking", or "how to lose weight" and "diabetes" itself, mentioned PTI report.

People are increasingly turning to the internet to clarify medical queries which inspired this innovation. According to researchers at the University of Warwick, 21.8% people in Britain chose to self-diagnose illnesses using the internet rather can a doctor in 2015.

Thus, search engine traces constitute a growing data pool and are now being accessed by researchers to design new-generation screening programs.

According to the PTI report, Nataliya Tkachenko from the University of Warwick, who led the study believes human online behaviors could help connect real-world human health landscape and synthetic, bio-centric monitoring tools. "Self-diagnosing behaviors online could be effectively leveraged for real-time health monitoring tools, with the biggest potential to be anticipated for chronic and non-communicable diseases", she said.

– prepared by Soha Kala of NewsGram. Twitter @SohaKala