Platform Aiming to Identify Health Problems Using AI Launching Alpha Version Within Weeks

A blockchain-based platform which bills itself as the "Future of artificial intelligence in healthcare" is preparing to launch an alpha version of its infrastructure within weeks.

Skychain believes its diagnostics system - a "Distributed open network" of artificial neural networks - can identify conditions in patients and prescribe appropriate treatments in milliseconds, substantially reducing the risk of human error during the crucial diagnosis stage.

By June, the company says early participants including hospitals, medical AI developers and healthcare data providers will have access to a "Fully built" ecosystem.

Skychain wants all of its plans to be "Completely realized" by next summer, when it plans to officially launch - paving the way for it to become "a leader in the medical AI market." Estimates by IBM indicate this industry could eventually be worth $200 bln, with the company setting the ambitious objective of dominating the sector with a market share of 70 percent.

The financial and human cost of medical errorsAccording to Skychain, medical errors occur on such a large scale that they have become the third most common cause of death in the US. One example can be found when doctors are analyzing X-ray images - with early cases of lung cancer misdiagnosed in two in three cases.

Skychain aspires to reduce the number of premature deaths from medical errors by a staggering 10 mln within a 10-year period - and last year, a prototype which pitted its AI technology against doctors was put to the test.

The results, as yet unverified, indicate that the technology was more effective at diagnosing skin, lung and cardiovascular diseases than some "Highly experienced" medical professionals.

Skychain told Cointelegraph: "In real life, medical professionals may get tired or be in low spirits; they may also lack the necessary experience, specialize in a different area, or be biased."Each of these factors can have a negative impact on the accuracy of a diagnosis.

A machine learning system can easily analyze a poorly structured medical history or wade through large amounts of data.

In the months and years to come, the company is confident of solving the problems which is preventing the medical AI market from flourishing.