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深度学习用于预测间歇性肺部疾病的急性恶化和死亡率

Ryo Teramachi1, Taiki Furukawa2, Yasuhiro Kondoh3

  • 1Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Annals of the American Thoracic Society
|December 16, 2024
PubMed
概括

一个新的深度学习模型准确地预测了使用纵向数据的患者间歇性肺病 (AE-ILD) 或死亡率的急性恶化. 这一进步有助于识别高风险个体,以便及时制定治疗策略.

关键词:
急性恶化的急性恶化.空气污染 空气污染深度学习是一种深度学习.间歇性肺病 间歇性肺病死亡率 死亡率

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