人工智能在MM成像中的现状和未来:系统性审查
Ehsan Alipour1,2, Atefe Pooyan1, Firoozeh Shomal Zadeh1
1Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98195, USA.
Diagnostics (Basel, Switzerland)
|November 14, 2023
概括
人工智能 (AI) 在多发性骨髓瘤 (MM) 成像方面表现有前途. 人工智能模型有效地使用成像数据来诊断和管理MM,放射学和细分是关键应用.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 多发性骨髓瘤 (MM) 是一种常见的血液性恶性瘤,需要成像用于诊断和管理.
- 人工智能 (AI) 越来越多地用于医疗状况的检测和管理.
研究的目的:
- 审查当前的文献和AI研究的趋势,特别是用于多发性骨髓瘤 (MM) 成像.
- 用CLAIM标准评估MM成像中的AI研究质量.
主要方法:
- 按照PRISMA指南进行系统的文献审查.
- 使用关键词搜索了PubMed,Embase和科学网:"人工智能"",放射学检查"",多发性骨髓瘤".
- 通过使用医疗成像人工智能检查清单 (CLAIM) 标准评估了14项选定的研究.
主要成果:
- 放射学分析和细分任务是MM成像中最常见的AI应用 (10/14研究).
- 放射学研究的重点是区分MM骨病变和预测复发.
- 分段研究旨在开发MM结构的自动化算法,实现从0.80到0.97.9的Dice分数.
结论:
- 医学成像是医疗保健中人工智能模型的宝贵数据来源.
- 人工智能在MM成像中,特别是通过放射学和细分,正在推进疾病管理.
- 需要进一步评估研究质量,正如CLAIM标准评估所指出的那样.
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