研究人员开发了人工智能模型,以更好地识别需要血液稀释剂、改进治疗的神经纤维化患者。 Researchers developed AI models to better identify atrial fibrillation patients who need blood thinners, improving treatment.

来自UCSF和Sinai山的研究人员开发了AI模型,帮助确定需要血液稀释剂以防止中风的神经纤维化病人。 Researchers from UCSF and Mount Sinai have developed AI models that help identify atrial fibrillation patients who need blood thinners to prevent strokes. 这些模型分析病人的医疗数据,以确定中风与出血的风险,有可能减少不必要的治疗,改善病人的结果。 These models analyze patients' medical data to determine the risk of stroke versus bleeding, potentially reducing unnecessary treatments and improving patient outcomes. 这些研究表明,人们应该转向更个性化的心房治疗方案. The studies suggest a shift towards more personalized treatment plans for atrial fibrillation.