子宫腺肌病
人工智能应用
人工智能
医学物理学
医学
子宫肌瘤
医学影像学
计算机科学
领域(数学)
专家系统
机器学习
无线电技术
专家意见
工程类
计算机断层摄影术
一次性
子宫内膜异位症
诊断准确性
作者
Morgan Briggs,Ayesha Saif,Timothy L. Kline,Wendaline VanBuren,Sarah L. Cohen Rassier,Isabel C Green
标识
DOI:10.1097/grf.0000000000000984
摘要
What was done? A review of artificial intelligence (AI) applications for the imaging of uterine fibroids, endometriosis, and adenomyosis. What was found? AI models can assist with the recognition, segmentation, and localization of uterine fibroids, and the differentiation of benign fibroids and sarcomas. Models can aid in the diagnosis of adenomyosis and endometriosis, and the prediction of the impact of endometriosis on fertility. What the findings mean? Deployed thoughtfully, AI tools could reduce variability, shorten read times, and add objective measurements to routine care. Studies evaluating these models are limited by single-institution designs and continued reliance on expert sonologists and radiologists.
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