Researchers from the University of Texas Health Science Center at Houston (UTHealth) have recently created a machine learning algorithm that can help physicians in deciding how to treat a patient's stroke. The artificial intelligence (AI) driven technology is designed to assist doctors outside of major stroke treatment facilities in determining whether an ischemic stroke patient would benefit from undergoing an endovascular procedure that removes the blood clot. Their work was published online on September 24 in the journal Stroke. This procedure, endovascular thrombectomy, is performed to remove an arterial blood clot causing an ischemic stroke. It involves the insertion of a catheter into the femoral artery of the thigh, which is followed to the patient's brain where the clot must be removed.

One in six people will suffer from stroke in their lifetime. Of the estimated 15 million victims worldwide, 6 million die every year and another 6 million are permanently disabled. Worse, the incidence of strokes is increasing, especially among people under age 55. By 2050, the number of strokes will have more than doubled, according to the American Stroke Association. Annual costs of stroke in the European Union alone are estimated at $53.1 billion.