Blog: Machines Just Got Better than Humans at Predicting Death – Newsweek
A machine-learning technology has surpassed human capabilities when it comes to predicting the chances of death or heart attacks, according to research presented today at the International Conference on Nuclear Cardiology and Cardiac in Lisbon, Portugal.
In testing, the algorithm, known as LogitBoost, analyzed 85 different variables from 950 patients—for which the researchers had followed for six years—identifying which of the participants had died or suffered heart attacks with an accuracy of more than 90 percent.
Machine learning (ML) is a form of artificial intelligence in which algorithms become better and better at predicting a given outcome without being explicitly programmed—usually through the intake of increasing amounts of data.
“These advances are far beyond what has been done in medicine, where we need to be cautious about how we evaluate risk and outcomes,” Luis Eduardo Juarez-Orozco, an author of the research from the Turku PET Centre, Finland, said in a statement. “We have the data but we are not using it to its full potential yet.”
When doctors are determining the best course of action for treating a patient, they often use things called “risk scores,” however, these are only based on a small number of variables, and thus can sometimes be inaccurate. Machine learning, on the other hand, can take into account many more variables, meaning it can predict outcomes with greater accuracy in many circumstances.
“Humans have a very hard time thinking further than three dimensions (a cube) or four dimensions (a cube through time,)” Juarez-Orozco explained: “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.”
Nine-hundred-and-fifty patients with chest pain took part in the study, and the researchers collected data from them on several measures which they inputted into the ML technology. This included information taken from CT scans about coronary health, medical records, sex, age, smoking status, and other variables.
In the six years that the scientists followed the participants, 24 had heart attacks and 49 died from any cause. When given the data, LogitBoot was able to correctly predict these outcomes with a more than 90 percent accuracy by continuously analysing the data over and over again.
“The algorithm progressively learns from the data and after numerous rounds of analyses, it figures out the high dimensional patterns that should be used to efficiently identify patients who have the event,” Juarez-Orozco. “The result is a score of individual risk.”
“Doctors already collect a lot of information about patients—for example those with chest pain,” Juarez-Orozco. “We found that machine learning can integrate these data and accurately predict individual risk. This should allow us to personalise treatment and ultimately lead to better outcomes for patients.”
Machine learning is a form of artificial intelligence in which algorithms become better at predicting a given outcome without being explicitly programmed. Chris McGrath/Getty Images