Patients with traumatic brain injury (TBI) often experience pathological increases in intracranial pressure (ICP), leading to intracranial hypertension (tIH), a common and serious complication. Early warning of an impending rise in ICP could potentially improve patient outcomes by enabling preemptive clinical intervention. However, the limited availability of patient data poses a challenge in developing reliable prediction models. In this study, we aim to determine whether foundation models, which leverage transfer learning, may offer a promising solution.

翻译：创伤性脑损伤（TBI）患者常经历颅内压（ICP）的病理性升高，导致颅内高压（tIH），这是一种常见且严重的并发症。对即将发生的ICP升高进行早期预警，可能通过实现先发性的临床干预来改善患者预后。然而，患者数据的有限性对开发可靠的预测模型构成了挑战。在本研究中，我们旨在确定利用迁移学习的基础模型是否可能提供一个有前景的解决方案。