将知识转化为行动:用人工智能支持的多学科肿瘤学建立更美好的未来。

Q1 Medicine
Arturo Loaiza-Bonilla, Nikhil Thaker, Caroline Chung, Ravi Bharat Parikh, Shawn Stapleton, Piotr Borkowski
{"title":"将知识转化为行动:用人工智能支持的多学科肿瘤学建立更美好的未来。","authors":"Arturo Loaiza-Bonilla, Nikhil Thaker, Caroline Chung, Ravi Bharat Parikh, Shawn Stapleton, Piotr Borkowski","doi":"10.1200/EDBK-25-100048","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and treat cancer. From earlier and more accurate diagnoses to personalized treatment planning, AI's impact is evident across radiology, pathology, radiation oncology, and medical oncology. By leveraging vast and diverse data-including imaging, genomic, clinical, and real-world evidence-AI algorithms can uncover complex patterns, accelerate drug discovery, and help identify optimal treatment regimens for each patient. However, realizing the full potential of AI also necessitates addressing concerns regarding data quality, algorithmic bias, explainability, privacy, and regulatory oversight-especially in low- and middle-income countries (LMICs), where disparities in cancer care are particularly pronounced. This study provides a comprehensive overview of how AI is reshaping cancer care, reviews its benefits and challenges, and outlines ethical and policy implications in line with ASCO's 2025 theme, <i>Driving Knowledge to Action.</i> We offer concrete calls to action for clinicians, researchers, industry stakeholders, and policymakers to ensure that AI-driven, patient-centric oncology is accessible, equitable, and sustainable worldwide.</p>","PeriodicalId":37969,"journal":{"name":"American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting","volume":"45 3","pages":"e100048"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.\",\"authors\":\"Arturo Loaiza-Bonilla, Nikhil Thaker, Caroline Chung, Ravi Bharat Parikh, Shawn Stapleton, Piotr Borkowski\",\"doi\":\"10.1200/EDBK-25-100048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and treat cancer. From earlier and more accurate diagnoses to personalized treatment planning, AI's impact is evident across radiology, pathology, radiation oncology, and medical oncology. By leveraging vast and diverse data-including imaging, genomic, clinical, and real-world evidence-AI algorithms can uncover complex patterns, accelerate drug discovery, and help identify optimal treatment regimens for each patient. However, realizing the full potential of AI also necessitates addressing concerns regarding data quality, algorithmic bias, explainability, privacy, and regulatory oversight-especially in low- and middle-income countries (LMICs), where disparities in cancer care are particularly pronounced. This study provides a comprehensive overview of how AI is reshaping cancer care, reviews its benefits and challenges, and outlines ethical and policy implications in line with ASCO's 2025 theme, <i>Driving Knowledge to Action.</i> We offer concrete calls to action for clinicians, researchers, industry stakeholders, and policymakers to ensure that AI-driven, patient-centric oncology is accessible, equitable, and sustainable worldwide.</p>\",\"PeriodicalId\":37969,\"journal\":{\"name\":\"American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting\",\"volume\":\"45 3\",\"pages\":\"e100048\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1200/EDBK-25-100048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1200/EDBK-25-100048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/2 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

人工智能(AI)正在以前所未有的速度改变多学科肿瘤学,重新定义临床医生如何检测、分类和治疗癌症。从更早、更准确的诊断到个性化的治疗计划,人工智能在放射学、病理学、放射肿瘤学和医学肿瘤学领域的影响是显而易见的。通过利用大量多样的数据,包括成像、基因组、临床和现实世界的证据,人工智能算法可以发现复杂的模式,加速药物发现,并帮助确定每位患者的最佳治疗方案。然而,实现人工智能的全部潜力还需要解决数据质量、算法偏差、可解释性、隐私和监管监督等问题,特别是在癌症治疗差距特别明显的低收入和中等收入国家。本研究全面概述了人工智能如何重塑癌症治疗,回顾了其益处和挑战,并概述了符合ASCO 2025主题的伦理和政策影响,将知识转化为行动。我们为临床医生、研究人员、行业利益相关者和政策制定者提出了具体的行动呼吁,以确保人工智能驱动的、以患者为中心的肿瘤学在全球范围内是可获得的、公平的和可持续的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.

Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and treat cancer. From earlier and more accurate diagnoses to personalized treatment planning, AI's impact is evident across radiology, pathology, radiation oncology, and medical oncology. By leveraging vast and diverse data-including imaging, genomic, clinical, and real-world evidence-AI algorithms can uncover complex patterns, accelerate drug discovery, and help identify optimal treatment regimens for each patient. However, realizing the full potential of AI also necessitates addressing concerns regarding data quality, algorithmic bias, explainability, privacy, and regulatory oversight-especially in low- and middle-income countries (LMICs), where disparities in cancer care are particularly pronounced. This study provides a comprehensive overview of how AI is reshaping cancer care, reviews its benefits and challenges, and outlines ethical and policy implications in line with ASCO's 2025 theme, Driving Knowledge to Action. We offer concrete calls to action for clinicians, researchers, industry stakeholders, and policymakers to ensure that AI-driven, patient-centric oncology is accessible, equitable, and sustainable worldwide.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊介绍: The Ed Book is a National Library of Medicine–indexed collection of articles written by ASCO Annual Meeting faculty and invited leaders in oncology. Ed Book was launched in 1985 to highlight standards of care and inspire future therapeutic possibilities in oncology. Published annually, each volume highlights the most compelling research and developments across the multidisciplinary fields of oncology and serves as an enduring scholarly resource for all members of the cancer care team long after the Meeting concludes. These articles address issues in the following areas, among others: Immuno-oncology, Surgical, radiation, and medical oncology, Clinical informatics and quality of care, Global health, Survivorship.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信