Gestational diabetes mellitus is a common pregnancy complication associated with significant adverse health outcomes for both women and infants. Effective screening and early prediction tools as part of routine clinical care are needed to reduce the impact of the disease on the baby and mother. Using large-scale electronic health records, Artzi and colleagues developed and evaluated a machine learning driven tool to identify women at high and low risk of GDM. Their findings showcase how artificial intelligence approaches can potentially be embedded in clinical care to enable accurate and rapid risk stratification.

中文翻译：

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预测妊娠糖尿病风险的电子健康记录。

妊娠期糖尿病是一种常见的妊娠并发症，对妇女和婴儿都有严重的不良健康后果。需要有效的筛查和早期预测工具作为常规临床护理的一部分，以减少疾病对婴儿和母亲的影响。Artzi 及其同事使用大规模电子健康记录开发并评估了一种机器学习驱动工具，以识别 GDM 高风险和低风险女性。他们的发现展示了人工智能方法如何潜在地嵌入临床护理以实现准确快速的风险分层。