Artificial intelligence can predict premature death, study finds

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The team of healthcare data scientists and doctors have developed and tested a system of computer-based'machine learning' algorithms to predict the risk of early death due to chronic disease in a large middle-aged population. They found this AI system was very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts. The study is published by PLOS ONE in a special collections edition of "Machine Learning in Health and Biomedicine." The team used health data from just over half a million people aged between 40 and 69 recruited to the UK Biobank between 2006 and 2010 and followed up until 2016. Leading the work, Assistant Professor of Epidemiology and Data Science, Dr Stephen Weng, said: "Preventative healthcare is a growing priority in the fight against serious diseases so we have been working for a number of years to improve the accuracy of computerised health risk assessment in the general population. Most applications focus on a single disease area but predicting death due to several different disease outcomes is highly complex, especially given environmental and individual factors that may affect them. "We have taken a major step forward in this field by developing a unique and holistic approach to predicting a person's risk of premature death by machine-learning.


AI system may predict premature death risk - Express Computer

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Scientists have developed and tested an artificial intelligence (AI)-based computer system to predict the risk of early death due to chronic diseases in a large middle-aged population. The system of computer-based'machine learning' algorithms was very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts, according to the study published in the journal PLOS ONE. Researchers at the University of Nottingham in the UK used health data from over half a million people aged between 40 and 69 recruited to the UK Biobank between 2006 and 2010 and followed up until 2016. "Most applications focus on a single disease area but predicting death due to several different disease outcomes is highly complex, especially given environmental and individual factors that may affect them," said Stephen Weng, Assistant Professor at the University of Nottingham. "We have taken a major step forward in this field by developing a unique and holistic approach to predicting a person's risk of premature death by machine-learning," Weng said in a statement.


When am AI going to die? Artificial intelligence model 'very accurately' predicts when it will occur

Daily Mail - Science & tech

AI may be able to predict when patients battling chronic diseases will die, research suggests. Scientists and doctors used data from half a million people to develop the tool that foresees who is at risk of an early death. It takes into account everything from a patient's family history of disease and how much salt they eat, to medication use and whether they wear sunscreen. Researchers said the AI system was'very accurate' in tests and around 10 per cent more reliable than estimations by existing machine-learning systems. The research was carried out by the University of Nottingham and led by Dr Stephen Weng, an assistant professor of epidemiology and data science.


AI could predict how much time people have left to live by analyzing body scans

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A computer could automatically assess scans to see potential health risks before they become obvious. There's an elusive innovation that would revolutionize medicine: a way to detect disease before it becomes obvious. A study recently published in the journal Scientific Reports could bring us a step closer to that capability. The paper reveals how artificial intelligence analyses of routine medical scans could be turned into powerful predictors of a person's health and risk of death. For the study, researchers used a machine learning algorithm to analyze routine chest CT scans from 48 adults, all of whom were over 60 years of age.


Artificial intelligence can accurately predict future heart disease and strokes, study finds

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Computers that can teach themselves from routine clinical data are potentially better at predicting cardiovascular risk than current standard medical risk models, according to new research at the University of Nottingham. The team of primary care researchers and computer scientists compared a set of standard guidelines from the American College of Cardiology (ACC) with four'machine-learning' algorithms – these analyse large amounts of data and self-learn patterns within the data to make predictions on future events – in this case, a patient's future risk having of heart disease or a stroke. The results, published in the online journal PLOS ONE, showed that the self-teaching'artificially intelligent' tools were significantly more accurate in predicting cardiovascular disease than the established algorithm. In computer science, the AI algorithms that were used are called'random forest', 'logistic regression', 'gradient boosting' and'neural networks'. Dr Stephen Weng, from the university's NIHR School for Primary Care Research, said: "Cardiovascular disease is the leading cause of illness and death worldwide.