论文标题

基于图像的人工智能在伤口评估中:系统评价

Image Based Artificial Intelligence in Wound Assessment: A Systematic Review

论文作者

Anisuzzaman, D. M., Wang, Chuanbo, Rostami, Behrouz, Gopalakrishnan, Sandeep, Niezgoda, Jeffrey, Yu, Zeyun

论文摘要

对急性和慢性伤口的有效评估可以帮助伤口护理团队在临床实践中大大改善伤口诊断,优化治疗计划,缓解工作量并实现与患者人群的健康相关生活质量。尽管人工智能(AI)在与健康相关的科学和技术中发现了广泛的应用,但基于AI的系统仍有待临床和计算开发,以用于高质量的伤口护理。为此,我们已经对基于智能图像的数据分析和系统开发进行了系统评估,以进行伤口评估。具体而言,我们对有关伤口测量(分段)和伤口诊断(分类)的研究方法进行了广泛的综述。我们还审查了有关伤口评估系统(包括硬件,软件和移动应用程序)的最新工作。从各种出版物数据库和在线资源中检索了250多种文章,其中115条经过精心选择,以涵盖最近和相关工作的广度和深度,以将当前的审查传达给其实现。

Efficient and effective assessment of acute and chronic wounds can help wound care teams in clinical practice to greatly improve wound diagnosis, optimize treatment plans, ease the workload and achieve health related quality of life to the patient population. While artificial intelligence (AI) has found wide applications in health-related sciences and technology, AI-based systems remain to be developed clinically and computationally for high-quality wound care. To this end, we have carried out a systematic review of intelligent image-based data analysis and system developments for wound assessment. Specifically, we provide an extensive review of research methods on wound measurement (segmentation) and wound diagnosis (classification). We also reviewed recent work on wound assessment systems (including hardware, software, and mobile apps). More than 250 articles were retrieved from various publication databases and online resources, and 115 of them were carefully selected to cover the breadth and depth of most recent and relevant work to convey the current review to its fulfillment.

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