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Voiding Cystourethrography (VCUG) and Cystography are specialized radiographic procedures used to examine the structure and function of the bladder and urethra.Voiding Cystourethrography (VCUG)A Voiding Cystourethrogram (VCUG) is a diagnostic imaging procedure that assesses the anatomy and function of the lower urinary tract. It focuses on the bladder, bladder neck, and urethra, helping detect abnormalities such as vesicoureteral reflux (VUR)—the backward or reverse flow of urine into the...

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一个基于机器学习的诺莫格拉姆模型,用于预测囊炎的复发.

Xuhao Liu1, Yuhang Wang1, Yinzhao Wang1

  • 1Department of Urology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China.

Therapeutic advances in urology
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概括

这项研究开发了一种使用机器学习来预测囊炎的复发的诺姆图,识别了尿道感染和血细胞计数等关键因素,以更好地管理患者.

关键词:
囊炎 腺状囊炎机器学习是机器学习.这个名字是名ogramogram.复发性 复发性 复发性

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科学领域:

  • 泌尿器科 泌尿器科 泌尿器科 泌尿器科
  • 炎症性疾病 炎症性疾病
  • 医疗信息学 医疗信息学

背景情况:

  • 囊炎是一种慢性尿道系统炎症性疾病,复发率高.
  • 囊炎腺体复发的根本原因仍然在很大程度上是未知的.
  • 了解复发因素对于有效的患者管理至关重要.

研究的目的:

  • 为了确定囊炎腺体炎复发的预测因素.
  • 为预测复发而开发一个预后诺莫格拉姆.
  • 建立一个简单可行的模型,用于临床应用.

主要方法:

  • 机器学习技术被用来识别复发的关键预测因素.
  • 使用已识别的预测因素构建了一个名ogram.
  • 模型性能使用接收机操作特征曲线分析,决策曲线分析和校准曲线来验证.

主要成果:

  • 这项研究包括252名患者,12个月复发率为57.14%.
  • 确定了5种复发的预测因素:尿道感染,尿路结石,乙素细胞计数,淋巴细胞计数和血清.
  • 开发的名图表显示出良好的预测性能,AUC值超过0.75.

结论:

  • 已经开发出一种可靠的基于机器学习的nomogram,用于预测囊炎腺体炎的复发.
  • 这种名图可以帮助识别患有复发高风险的患者.
  • 该模型为临床预测和管理策略提供了一个可行的工具.