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研究人员利用数据挖掘方法为抑郁症患者提供有效的处方

2017-12-09 MedSci MedSci原创

数据挖掘方法抑郁症
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个性化医疗是近年来最有前途的医学发展之一，这就决定了哪些病人将从各种治疗中获益。马萨诸塞州综合医院(MGH)和哈佛大学(Harvard University)的一项新研究发现，使用这些模型中的电子病历数据可能会带来很大的希望。抑郁症是一种众所周知的难以治疗的疾病，病人在找到有效的药物之前，常常需要尝试几种不同的药物。研究人员--由博士后研究员迈克尔·休斯（Michael Hughes）加入的MGH

个性化医疗是近年来最有前途的医学发展之一，这就决定了哪些病人将从各种治疗中获益。马萨诸塞州综合医院(MGH)和哈佛大学(Harvard University)的一项新研究发现，使用这些模型中的电子病历数据可能会带来很大的希望。抑郁症是一种众所周知的难以治疗的疾病，病人在找到有效的药物之前，常常需要尝试几种不同的药物。研究人员--由博士后研究员迈克尔·休斯（Michael Hughes）加入的MGH的Roy Perlis和哈佛的Finale Doshi-Velez--检查了5万多抑郁症患者的医疗记录中的大量电子数据。通过应用机器学习，他们能够将数据分类为抑郁症亚型，由数据突出的症状和特征组成，如年龄、性功能障碍、体重增加或肥胖。Doshi-Velez的研究小组还研究了最终成功治疗患者抑郁症的16种抗抑郁药。从这些数据中，他们能够开发一种算法来预测基于抑郁症亚型的抗抑郁药的有效性。在临床实施时，新工具被发现比现有方法更准确。此外，研究人员所调查的临床医生表示，他们发现该工具比现有的预测模型更方便用户使用。由于第一次治疗抑郁症的患者有50％的失败率，第二种治疗方法的失败率是50％，所以减少内

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    2018-09-05 gostraight

    #研究人员#

    0

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    2018-09-16 xiongke010

    #抑郁症患者#

    0

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    2017-12-10 lyh994

    医学大数据运用

    0

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    2017-12-10 飛歌

    学习了很有用不错

    0

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