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

IF 2.3 4区 医学 Q2 HEMATOLOGY Expert Review of Hematology Pub Date : 2024-10-01 Epub Date: 2024-08-13 DOI:10.1080/17474086.2024.2389997
Andrew Srisuwananukorn, Jordan E Krull, Qin Ma, Ping Zhang, Alexander T Pearson, Ronald Hoffman
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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.

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人工智能在骨髓增生性肿瘤中的应用:综述。
引言人工智能(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预测相关结果的潜力。目前,用于预测骨髓增生性肿瘤(MPN)临床结果的人工智能正在研究中:在这篇叙述性综述中,我们讨论了利用临床可用数据或实验室实验结果改善 MPN 临床护理的人工智能研究。通过查询 PubMed 和美国血液学会会议,我们找到了 2000 年至 2023 年期间的摘要和手稿。总体而言,多学科研究人员已开发出人工智能方法,试图提高多发性骨髓瘤的诊断准确性、风险预测、治疗选择或进行临床前研究,以确定作为新型治疗药物的候选分子:我们的专家认为,人工智能方法在多发性骨髓瘤护理和血液学领域的应用将继续增长,临床实用性也将不断提高。我们相信,如果能根据人工智能特定的监管指南进行适当开发,人工智能模型将作为临床决策支持工具为医护人员提供帮助。虽然本综述中报告的研究结果只是人工智能在多发性骨髓瘤中的早期研究,但研究界的集体工作为改善未来多发性骨髓瘤临床护理的决策制定提供了一个前景广阔的框架。
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来源期刊
CiteScore
4.70
自引率
3.60%
发文量
98
审稿时长
6-12 weeks
期刊介绍: Advanced molecular research techniques have transformed hematology in recent years. With improved understanding of hematologic diseases, we now have the opportunity to research and evaluate new biological therapies, new drugs and drug combinations, new treatment schedules and novel approaches including stem cell transplantation. We can also expect proteomics, molecular genetics and biomarker research to facilitate new diagnostic approaches and the identification of appropriate therapies. Further advances in our knowledge regarding the formation and function of blood cells and blood-forming tissues should ensue, and it will be a major challenge for hematologists to adopt these new paradigms and develop integrated strategies to define the best possible patient care. Expert Review of Hematology (1747-4086) puts these advances in context and explores how they will translate directly into clinical practice.
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