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人工智能在骨髓增殖性肿瘤中的应用:综述

Applications of artificial intelligence to myeloproliferative neoplasms: a narrative review.

机构信息

Division of Hematology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.

出版信息

Expert Rev Hematol. 2024 Oct;17(10):669-677. doi: 10.1080/17474086.2024.2389997. Epub 2024 Aug 13.

Abstract

INTRODUCTION

Artificial intelligence (AI) is a rapidly growing field of computational research with the potential to extract nuanced biomarkers for the prediction of outcomes of interest. AI implementations for the prediction for clinical outcomes for myeloproliferative neoplasms (MPNs) are currently under investigation.

AREAS COVERED

In this narrative review, we discuss AI investigations for the improvement of MPN clinical care utilizing either clinically available data or experimental laboratory findings. Abstracts and manuscripts were identified upon querying PubMed and the American Society of Hematology conference between 2000 and 2023. Overall, multidisciplinary researchers have developed AI methods in MPNs attempting to improve diagnostic accuracy, risk prediction, therapy selection, or pre-clinical investigations to identify candidate molecules as novel therapeutic agents.

EXPERT OPINION

It is our expert opinion that AI methods in MPN care and hematology will continue to grow with increasing clinical utility. We believe that AI models will assist healthcare workers as clinical decision support tools if appropriately developed with AI-specific regulatory guidelines. Though the reported findings in this review are early investigations for AI in MPNs, the collective work developed by the research community provides a promising framework for improving decision-making in the future of MPN clinical care.

摘要

简介

人工智能(AI)是一个快速发展的计算研究领域,具有提取细微生物标志物以预测感兴趣结果的潜力。目前正在研究用于预测骨髓增生性肿瘤(MPN)临床结果的 AI 实现。

涵盖领域

在这篇叙述性评论中,我们讨论了利用临床可用数据或实验实验室发现来改善 MPN 临床护理的 AI 研究。通过在 2000 年至 2023 年期间查询 PubMed 和美国血液学会会议,确定了摘要和手稿。总的来说,多学科研究人员已经在 MPN 中开发了 AI 方法,试图提高诊断准确性、风险预测、治疗选择或临床前研究,以确定候选分子作为新型治疗剂。

专家意见

我们的专家意见是,MPN 护理和血液学中的 AI 方法将随着临床实用性的提高而继续增长。我们相信,如果根据 AI 特定的监管指南适当开发,AI 模型将作为临床决策支持工具来协助医疗保健工作者。尽管本评论中报告的 AI 在 MPN 中的发现是早期研究,但研究界的集体工作为改善未来 MPN 临床护理的决策提供了有希望的框架。

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