人工智能作为诊断心脏淀粉样变性的工具:系统性综述

IF 1.6 4区 医学 Q4 ENGINEERING, BIOMEDICAL
Armia Ahmadi-Hadad, Egle De Rosa, Luigi Di Serafino, Giovanni Esposito
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引用次数: 0

摘要

目的心脏淀粉样变性(CA)是一种诊断率极低的疾病,其特征是折叠错误的淀粉样蛋白片段在心脏中堆积,导致心脏功能减退和心肌僵硬。人工智能(AI)作为诊断包括淀粉样变性在内的心血管疾病的潜在工具,已经引起了人们的极大兴趣。本系统性综述集中探讨了人工智能在诊断 CA 中的应用。筛选过程分为两个阶段,采用预先确定的纳入和排除标准,并以盲法进行。结果经过筛选,共有 10 项研究被认为符合纳入本综述的条件。这些研究评估了分析常规实验室数据、病历、心电图、经胸超声心动图、CMR 和 WBS 的人工智能模型在 CA 诊断中的潜在作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial Intelligence as a Tool for Diagnosis of Cardiac Amyloidosis: A Systematic Review

Artificial Intelligence as a Tool for Diagnosis of Cardiac Amyloidosis: A Systematic Review

Purpose

Cardiac amyloidosis (CA) is a highly underdiagnosed disease characterized by the accumulation of misfolded amyloid protein fragments in the heart, resulting in reduced heart functionality and myocardial stiffness. Artificial intelligence (AI) has garnered considerable interest as a potential tool for diagnosing cardiovascular diseases, including CA. This systematic review concentrates on the application of AI in the diagnosis of CA.

Methods

A comprehensive systematic search was performed on the databases of PubMed, Embase, and Medline, to identify relevant studies. The screening process was conducted in two stages, using predetermined inclusion and exclusion criteria, and was carried out in a blinded manner. In cases where discrepancies arose, the reviewers discussed and resolved the issue through consensus.

Results

Following the screening process, a total of 10 studies were deemed eligible for inclusion in this review. These investigations evaluated the potential utility of AI models that analyzed routine laboratory data, medical records, ECG, transthoracic echocardiography, CMR, and WBS in the diagnosis of CA.

Conclusion

AI models have demonstrated utility as a diagnostic tool for CA, with comparable or in one case superior efficacy to that of expert cardiologists.

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来源期刊
CiteScore
4.30
自引率
5.00%
发文量
81
审稿时长
3 months
期刊介绍: The purpose of Journal of Medical and Biological Engineering, JMBE, is committed to encouraging and providing the standard of biomedical engineering. The journal is devoted to publishing papers related to clinical engineering, biomedical signals, medical imaging, bio-informatics, tissue engineering, and so on. Other than the above articles, any contributions regarding hot issues and technological developments that help reach the purpose are also included.
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