Medical Xpress July 25, 2024
Expensive MRI exams are commonly used to evaluate patients with suspected gallstones, often delaying definitive intervention and increasing the risk of disease severity, further complications and longer hospital stays.
Over a five-year period, five machine learning models were developed and tested to retrospectively predict patients’ risk of choledocholithiasis, all of which outperformed existing diagnostic guidelines. The results have been published in ANZ Journal of Surgery.
Professor of Surgery at the University of Tasmania School of Medicine and Fellow at the Royal Australasian College of Surgeons, Dr. Richard Turner, said he’s confident AI will play a strong role in the future of choledocholithiasis diagnoses.
“Choledocholithiasis accounts for approximately 15% of gallstone diagnoses, so it’s important we continually explore innovative technologies like...
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