The continuous improvement of digital assistance in the radiation oncologist's work: from web-based nomograms to the adoption of large-language models (LLMs). A systematic review by the young group of the Italian association of radiotherapy and clinical oncology (AIRO).

IF 9.7 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiologia Medica Pub Date : 2024-11-01 Epub Date: 2024-10-13 DOI:10.1007/s11547-024-01891-y
Antonio Piras, Ilaria Morelli, Riccardo Ray Colciago, Luca Boldrini, Andrea D'Aviero, Francesca De Felice, Roberta Grassi, Giuseppe Carlo Iorio, Silvia Longo, Federico Mastroleo, Isacco Desideri, Viola Salvestrini
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Abstract

Purpose: Recently, the availability of online medical resources for radiation oncologists and trainees has significantly expanded, alongside the development of numerous artificial intelligence (AI)-based tools. This review evaluates the impact of web-based clinical decision-making tools in the clinical practice of radiation oncology.

Material and methods: We searched databases, including PubMed, EMBASE, and Scopus, using keywords related to web-based clinical decision-making tools and radiation oncology, adhering to PRISMA guidelines.

Results: Out of 2161 identified manuscripts, 70 were ultimately included in our study. These papers all supported the evidence that web-based tools can be transversally integrated into multiple radiation oncology fields, with online applications available for dose and clinical calculations, staging and other multipurpose intents. Specifically, the possible benefit of web-based nomograms for educational purposes was investigated in 35 of the evaluated manuscripts. As regards to the applications of digital and AI-based tools to treatment planning, diagnosis, treatment strategy selection and follow-up adoption, a total of 35 articles were selected. More specifically, 19 articles investigated the role of these tools in heterogeneous cancer types, while nine and seven articles were related to breast and head & neck cancers, respectively.

Conclusions: Our analysis suggests that employing web-based and AI tools offers promising potential to enhance the personalization of cancer treatment.

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不断改进放射肿瘤学家工作中的数字辅助工具:从基于网络的提名图到采用大型语言模型(LLM)。意大利放射治疗和临床肿瘤学协会(AIRO)青年小组的系统回顾。
目的:最近,随着大量基于人工智能(AI)的工具的开发,放射肿瘤学家和受训人员可获得的在线医疗资源显著增加。本综述评估了基于网络的临床决策工具对放射肿瘤学临床实践的影响:我们使用与基于网络的临床决策工具和放射肿瘤学相关的关键词检索了包括PubMed、EMBASE和Scopus在内的数据库,并遵守了PRISMA指南:在2161篇已确认的手稿中,有70篇最终纳入了我们的研究。这些论文均支持网络工具可横向整合到多个放射肿瘤学领域的证据,其在线应用可用于剂量和临床计算、分期及其他多用途目的。具体而言,35 篇受评稿件研究了基于网络的提名图在教育方面可能带来的益处。关于数字和人工智能工具在治疗计划、诊断、治疗策略选择和后续治疗中的应用,共有 35 篇文章入选。更具体地说,19 篇文章研究了这些工具在不同癌症类型中的作用,9 篇和 7 篇文章分别与乳腺癌和头颈部癌症有关:我们的分析表明,采用基于网络和人工智能的工具有望提高癌症治疗的个性化程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Radiologia Medica
Radiologia Medica 医学-核医学
CiteScore
14.10
自引率
7.90%
发文量
133
审稿时长
4-8 weeks
期刊介绍: Felice Perussia founded La radiologia medica in 1914. It is a peer-reviewed journal and serves as the official journal of the Italian Society of Medical and Interventional Radiology (SIRM). The primary purpose of the journal is to disseminate information related to Radiology, especially advancements in diagnostic imaging and related disciplines. La radiologia medica welcomes original research on both fundamental and clinical aspects of modern radiology, with a particular focus on diagnostic and interventional imaging techniques. It also covers topics such as radiotherapy, nuclear medicine, radiobiology, health physics, and artificial intelligence in the context of clinical implications. The journal includes various types of contributions such as original articles, review articles, editorials, short reports, and letters to the editor. With an esteemed Editorial Board and a selection of insightful reports, the journal is an indispensable resource for radiologists and professionals in related fields. Ultimately, La radiologia medica aims to serve as a platform for international collaboration and knowledge sharing within the radiological community.
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