AI identifies bladder cancer early
Researchers have developed an artificial intelligence system capable of identifying bladder cancer patients five years before their official diagnosis, enabling early detection and increasing survival rates. The system is based on analyzing electronic health records of approximately 70,000 patients and successfully detected cancer with 91% accuracy up to five years prior to symptom onset and before diagnosis, identifying about 85% of cases. The model relies on uncovering hidden patterns in the data that include risk factors and early symptoms, outperforming current screening guidelines which mainly depend on visible blood in the urine. The findings suggest the potential to improve screening procedures and reduce unnecessary surgical interventions by classifying patients according to their risk level. This technology represents a significant step toward early detection of bladder cancer, one of the most common types, especially given the lack of routine screening programs. It highlights the importance of AI-driven innovations in improving treatment outcomes and survival rates.
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