One of the keys to a healthy life is prevention and early detection of diseases. A new study published in npj Digital Medicine, a Nature Portfolio journal, shows how artificial intelligence machine learning has the potential to accelerate personalized medicine by providing a patient’s risk of developing two or more disease diagnoses decades in advance by identifying disease trajectories.

“Early detection and identification of a patient’s projected disease trajectory might enable prompt and timely treatments next to targeted preventive action,” wrote Peter Klimek, Ph.D., the study’s corresponding author, recipient of the Club of Education and Science Journalists’ 2021 Austrian Scientist of the Year award, and faculty member of the Medical University of Vienna (MedUni) Vienna’s Complexity Science Hub, along with co-authors Elma Dervić, Johannes Sorger, Liuhuaying Yang, Michael Leutner, Alexander Kautzky, Stefan Thurner, and Alexandra Kautzky-Willer.

The study used a massive dataset of 44 million records of hospital stays from 2003 to 2014, selected from an electronic health registry database consisting of 8.9 million patients, nearly the entire population, from all hospitals in Austria from 1997 through 2014.

Having a large training dataset favorably affects the overall performance of the algorithm. AI machine........

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