人工智能在心脏肿瘤学中的应用、挑战及未来发展方向

IF 4.4 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Francesco Ravera, Nicolò Gilardi, Alberto Ballestrero, Gabriele Zoppoli
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引用次数: 0

摘要

与癌症治疗相关的心脏毒性管理已成为一个重大的临床挑战,促使心脏肿瘤学快速发展。随着癌症治疗变得越来越复杂,越来越需要加强诊断和治疗策略来管理其心血管副作用。目的本综述探讨了人工智能(AI)通过整合不同的数据来源来解决心脏毒性管理的挑战,从而彻底改变心脏肿瘤学的潜力。方法探讨人工智能在心脏肿瘤学中的应用,重点关注其利用多种数据源的能力,包括电子健康记录、心电图、成像模式、可穿戴传感器和循环血清生物标志物。结果人工智能在改善心脏毒性的风险分层和纵向监测方面具有显著的潜力。通过优化心电图、非侵入性成像和循环生物标志物的使用,人工智能有助于早期检测、更好地预测结果,以及更个性化的治疗干预。这些进步有望提高患者的治疗效果并简化临床决策。人工智能通过提高诊断和治疗能力,代表了心脏肿瘤学的变革机会。然而,成功的实施需要解决实际的挑战,如数据集成、模型可解释性和临床医生培训。临床医生和人工智能开发人员之间的持续合作对于将人工智能完全整合到常规临床工作流程至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Applications, challenges and future directions of artificial intelligence in cardio-oncology

Applications, challenges and future directions of artificial intelligence in cardio-oncology

Background

The management of cardiotoxicity related to cancer therapies has emerged as a significant clinical challenge, prompting the rapid growth of cardio-oncology. As cancer treatments become more complex, there is an increasing need to enhance diagnostic and therapeutic strategies for managing their cardiovascular side effects.

Objective

This review investigates the potential of artificial intelligence (AI) to revolutionize cardio-oncology by integrating diverse data sources to address the challenges of cardiotoxicity management.

Methods

We explore applications of AI in cardio-oncology, focusing on its ability to leverage multiple data sources, including electronic health records, electrocardiograms, imaging modalities, wearable sensors, and circulating serum biomarkers.

Results

AI has demonstrated significant potential in improving risk stratification and longitudinal monitoring of cardiotoxicity. By optimizing the use of electrocardiograms, non-invasive imaging, and circulating biomarkers, AI facilitates earlier detection, better prediction of outcomes, and more personalized therapeutic interventions. These advancements are poised to enhance patient outcomes and streamline clinical decision-making.

Conclusions

AI represents a transformative opportunity in cardio-oncology by advancing diagnostic and therapeutic capabilities. However, successful implementation requires addressing practical challenges such as data integration, model interpretability, and clinician training. Continued collaboration between clinicians and AI developers will be essential to fully integrate AI into routine clinical workflows.

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来源期刊
CiteScore
9.50
自引率
3.60%
发文量
192
审稿时长
1 months
期刊介绍: EJCI considers any original contribution from the most sophisticated basic molecular sciences to applied clinical and translational research and evidence-based medicine across a broad range of subspecialties. The EJCI publishes reports of high-quality research that pertain to the genetic, molecular, cellular, or physiological basis of human biology and disease, as well as research that addresses prevalence, diagnosis, course, treatment, and prevention of disease. We are primarily interested in studies directly pertinent to humans, but submission of robust in vitro and animal work is also encouraged. Interdisciplinary work and research using innovative methods and combinations of laboratory, clinical, and epidemiological methodologies and techniques is of great interest to the journal. Several categories of manuscripts (for detailed description see below) are considered: editorials, original articles (also including randomized clinical trials, systematic reviews and meta-analyses), reviews (narrative reviews), opinion articles (including debates, perspectives and commentaries); and letters to the Editor.
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