Called crazy from past angiograms patients are classifie according to their risk of having a heart attack in 5 years . Spee is the key. What the AI reads in seconds for doctors usually requires almost 30 minutes per patient. Machine learning in the preiction of heart attacks The University of Nottingham use 4 machine learning algorithms to analyze data from almost 400000 people . They wante to know if the AIs studie had the ability to preict a heart attack. They entere data such as age sex body mass index meical history and laboratory values. The algorithms preicte the 10-year risk of each person having a heart attack.
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At the same time some doctors made their calculations in a manual and traditional way. The neural network machine learning systemone of 4 studie improve the preiction of cardiovascular events by 7.6. compare to meical ones. As the authors remark in their publication this means an aid to the professionals but not their replacement. The no photo editor code in preicting a heart attack No code technology is gaining ground. It is a model for creating applications and automatic information systems without the nee to know how to program. The use of this AI in healthcare increases accessibility and becomes more easily available to doctors.
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