深度学习预测脏异常用于产前超声波诊断
Olivier X Miguel1, Emily Kaczmarek2, Inok Lee1
1Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Scientific reports
|April 19, 2024
概括
深度学习模型显示,使用超声波对早期胎儿脏异常检测有前途. 新的解释方法提高了对尿路扩张和多囊性功能等疾病的预测准确度.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 产前诊断 在产前诊断
背景情况:
- 深度学习 (DL) 模型在临床诊断,特别是医学成像分析方面具有重大潜力.
- 早期发现胎儿脏异常对于及时干预和改善患者结果至关重要.
研究的目的:
- 通过使用产前超声波图像,研究深度学习模型在早期检测胎儿脏异常方面的有效性.
- 开发和评估用于医学诊断中的多类分类问题的新型模型解释技术.
主要方法:
- 利用深度学习算法分析了969张胎儿超声波图像的数据集.
- 员工适应了两类表示和多类模型解释方法.
- 应用可解释AI (XAI) 可视化工具,Grad-CAM和HiResCAM,用于模型解释性和错误分类分析.
主要成果:
- 性能最好的模型在ROC曲线下的交叉验证面积达到91.28%±0.52%.
- 总体准确率达到84.03%±0.76%,灵敏度为77.39%±1.99%和特异性为87.35%±1.28%.
- 这项研究成功地发现了单边尿路扩张 (259) 和单边多囊性功能失调 (64) 的病例.
结论:
- 深度学习模型显示出从有限的产前超声数据中预测胎儿脏异常的巨大潜力.
- 拟议的模型解释适应为医疗AI中复杂的多类预测挑战提供了一种新的解决方案.
- 这些进展可以帮助早期诊断和治疗先天性病.
相关概念视频
01:24Imaging Studies II: Ultrasonography
909
IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...
909
01:30Acute Kidney Injury IV: Diagnostic Studies and Prevention
559
Accurate diagnosis and effective prevention are critical in managing Acute Kidney Injury (AKI), which is linked to high mortality rates ranging from 10% to 80%. Timely recognition of at-risk patients and careful monitoring can significantly reduce the likelihood of kidney damage.Diagnostic Assessments:The diagnostic process starts with a comprehensive medical history to identify prerenal, intrarenal, and postrenal causes.Prerenal causes, such as dehydration, hypotension, or blood loss, should...
559