A malfunctioning ventriculoperitoneal (VP) shunt will typically cause a rise in intracranial pressure, which can be difficult to identify without costly imaging. Novel, state-of-the art machine learning techniques can be leveraged to develop an algorithm that noninvasively estimates intracranial pressure. The resulting algorithm will accurately determine the presence or absence of ventriculoperitoneal shunt malfunction in patients with hydrocephalus.