The new study, led by the University of Plymouth, presents an AI tool to analyze electronic health records to detect subtle warning signs of the disease—identifying early symptoms, risk factors and clinical activities that precede diagnosis. The work is published in the journal IEEE Transactions on Biomedical Engineering.

Uncovering hidden patterns in health data

Current referral guidelines focus primarily on visible blood in urine (hematuria), but this symptom can also indicate benign conditions like kidney stones or prostate issues. The result is a poor detection rate for bladder cancer, which can be fully confirmed only with a cystoscopy procedure (where a long, thin tube with a small camera inside is moved up the urethra and into the bladder).