A machine learning algorithm claims to predict heart attacks and death from heart disease with a degree of accuracy beating human practitioners.
The algorithm claims to have a 90 percent accuracy. LogitBoost was trained on data from 950 chest pain patients – from the data, 85 variables are calculated.
Each of the patients have known outcomes after six years. Combined, this algorithm was able to identify patterns which indicates a higher chance of a heart attack or cardiac-related death.
Study author Dr Luis Eduardo Juarez-Orozco, said these advances go beyond medicine.
He said: “These advances are far beyond what has been done in medicine, where we need to be cautious about how we evaluate risk and outcomes.
“We have the data but we are not using it to its full potential yet.”
The findings were presented yesterday at the International Conference on Nuclear Cardiology and Cardiac CT (ICNC) in Lisbon, Portugal.
Dr Juarez-Orozco said: “Humans have a very hard time thinking further than three dimensions or four dimensions.
“The moment we jump into the fifth dimension we’re lost.
“Our study shows that very high dimensional patterns are more useful than single dimensional patterns to predict outcomes in individuals and for that we need machine learning.”
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