Researchers at Carnegie Mellon University, Florida International University, and Santa Calovara University developed a model for diagnosing stroke that uses the rationale behind machine learning to work. An important difference from industrial production is that it works without the need for diachostical visualization of the internal organs of a person. But because it can be observed even where there is only a small set of equipment.
Diagnosis of stroke is extremely difficult due to specific diseases – for example, in 25% of cases characteristic contributions to mostro netto occurred. Mortality from misdiagnosed stroke is 30 times higher than heart attack. It is easy to confuse stroke cases with dozens of other diseases and disorders, so the likelihood of IKE in automaks is very high.
The new model was trained for 143 thousand rubles. medical records of patients of Floridas hospitals, the sample included people of vers times and ages. Testing has shown that she can detect ilt, or determine that it has happened in the past, with 84% confidence. The next model is below 30%. Odnoko the authors of the development of accessories that their model is not yet suitable for stand-alone use, it is used methods.
Source: Tech Cult
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