Using artificial intelligence to predict mortality

Log in with your Medical News Today account to create or edit your custom homepage, catch-up on your opinions notifications and set your newsletter preferences.Sign up for a free Medical News Today account to customize your medical and health news experiences.An increasing amount of recent research is suggesting that computer algorithms and artificial intelligence (AI) learning can prove highly useful in the medical world.For instance, a study that appeared a few months ago found that deep learning algorithms can accurately predict the onset of Alzheimer's disease as early as 6 years in advance.Using a so-called "training dataset," deep learning algorithms can "teach themselves" to predict if and when an event is likely to occur.Now, researchers have set out to examine whether machine learning can accurately predict premature mortality due to chronic disease.Stephen Weng, who is an assistant professor of epidemiology and data science at the University of Nottingham in the United Kingdom, led the new research. The UK Biobank study researchers clinically followed the participants until 2016.For the current study, Weng and team developed a system of learning algorithms using two models called "random forest" and "deep learning." They used the models to predict the risk of premature death due to chronic disease.The scientists examined the predictive accuracy of these models and compared them with conventional prediction models, such as "Cox regression" analysis and a multivariate Cox model. "This uses computers to build new risk prediction models that take into account a wide range of demographic, biometric, clinical, and lifestyle factors for each individual assessed, even their dietary consumption of fruit, vegetables, and meat per day," explains Weng.Furthermore, say the researchers, the results of the new study strengthen previous findings, which showed that certain AI algorithms are better at predicting heart disease risk than the conventional prediction models that cardiologists currently use."There is currently intense interest in the potential to use 'AI' or 'machine learning' to better predict health outcomes.