Researchers at Indiana University School of Medicine have developed and tested a six-point scoring system that can help identify patients at high risk of internal bleeding in damaged heart muscle after a severe heart attack using explainable artificial intelligence (XAI).
The scoring system is designed for interventional cardiologists to use in cardiac catheterization, or CATH labs before reopening a patient's blocked artery.
Researchers found that the scoring system could accurately predict IMH using clinical information already available during cardiac catheterization at the patient's bedside.
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