Researchers at the University of Leuven in Belgium said a study they conducted showed artificial intelligence could help interpret, and thereby improve, lung function tests used to diagnose long-term lung disease.
Results of the study were presented Monday at the European Respiratory Society's International Congress.
As part of the study, the researchers used data from 968 people who were undergoing complete lung function testing for the first time.
Using a concept called “machine learning”, they developed an algorithm that takes into account routine lung function parameters and clinical variables of smoking history, body mass index, and age to make a suggestion for the most likely diagnosis.
"We have demonstrated that artificial intelligence can provide us with a more accurate diagnosis in this new study,” Wim Janssens, senior author of the study, said. “The beauty of our development is that the algorithm can simulate the complex reasoning that a clinician uses to give their diagnosis, but in a more standardized and objective way so it removes any bias. "
Currently, clinicians rely on sifting through results using population-based parameters. By employing AI, the machine can observe a combination of patterns at one time to help produce a more accurate diagnosis.
Last week, Houston Methodist researchers announced they’re using artificial intelligence to quickly and accurately interpret patient charts to help physicians predict breast cancer risk, which they hope reduces unnecessary testing procedures performed as a result of false-positive mammograms.
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