Medicine

AI can help predict premature deaths

AI can help predict premature deaths

But in the not-too-distant future, AI could improve healthcare - by pinpointing people who are likely to succumb to preventable diseases.

Predictions by the AI were compared against information from the United Kingdom cancer registry, death records, and statistics on "hospital episodes" to determine its accuracy. The research team included more than 500,000 people aging between 40 and 69 for the study.

Researchers with the University of Nottingham have developed an artificial intelligence system that accurately predicted premature death in study participants.

As mentioned by Assistant Professor of Epidemiology and Data Science, Dr. Stephen Weng, "We mapped the resulting predictions to mortality data from the cohort, using Office of National Statistics death records, the United Kingdom cancer registry and "hospital episodes" statistics".

This new risk prediction models consider statistic, biometric, clinical and way of life factors for every person, and evaluate even their dietary utilization of organic product, vegetables and meat every day, said researchers.

"We mapped the resulting predictions to mortality data from the cohort, using Office of National Statistics death records, the United Kingdom cancer registry and 'hospital episodes" statistics.

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The predictions of early death that were made by AI algorithms were "significantly more accurate" than predictions delivered by a model that did not use machine learning, lead study author Dr. Stephen Weng, an assistant professor of epidemiology and data science at the University of Nottingham (UN) in the United Kingdom, said in a statement.

Published by PLOS ONE in a special collections edition of Machine Learning in Health and Biomedicine, the study showcases how useful the tools of AI and machine learning can be and its application across the medical fields.

When it comes to mortality prediction, Cox regression, which is traditionally used as a prediction model, shows the least accuracy.

"There is now intense interest in the potential to use "AI" or "machine-learning" to better predict health outcomes", said Professor Joe Kai, one of the clinical academics working on the project.

Now, researchers have set out to examine whether machine learning can accurately predict premature mortality due to chronic disease. However, the techniques can be hard to use and new to a number of health research professionals. Further research requires verifying and validating these AI algorithms in other population groups and exploring ways to implement these systems into routine healthcare.