Advancements and implications of artificial intelligence for early detection, diagnosis and tailored treatment of cancer

IF 3 3区医学 Q2 ONCOLOGY

Seminars in oncology Pub Date : 2025-05-08 DOI:10.1016/j.seminoncol.2025.152349

Sonia Chadha, Sayali Mukherjee, Somali Sanyal

{"title":"Advancements and implications of artificial intelligence for early detection, diagnosis and tailored treatment of cancer","authors":"Sonia Chadha, Sayali Mukherjee, Somali Sanyal","doi":"10.1016/j.seminoncol.2025.152349","DOIUrl":null,"url":null,"abstract":"<div><div>The complexity and heterogeneity of cancer makes early detection and effective treatment crucial to enhance patient survival and quality of life. The intrinsic creative ability of artificial intelligence (AI) offers improvements in patient screening, diagnosis, and individualized care. Advanced technologies, like computer vision, machine learning, deep learning, and natural language processing, can analyze large datasets and identify patterns that permit early cancer detection, diagnosis, management and incorporation of conclusive treatment plans, ensuring improved quality of life for patients by personalizing care and minimizing unnecessary interventions. Genomics, transcriptomics and proteomics data can be combined with AI algorithms to unveil an extensive overview of cancer biology, assisting in its detailed understanding and will help in identifying new drug targets and developing effective therapies. This can also help to identify personalized molecular signatures which can facilitate tailored interventions addressing the unique aspects of each patient. AI-driven transcriptomics, proteomics, and genomes represents a revolutionary strategy to improve patient outcome by offering precise diagnosis and tailored therapy. The inclusion of AI in oncology may boost efficiency, reduce errors, and save costs, but it cannot take the role of medical professionals. While clinicians and doctors have the final say in all matters, it might serve as their faithful assistant</div></div>","PeriodicalId":21750,"journal":{"name":"Seminars in oncology","volume":"52 3","pages":"Article 152349"},"PeriodicalIF":3.0000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminars in oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0093775425000417","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

The complexity and heterogeneity of cancer makes early detection and effective treatment crucial to enhance patient survival and quality of life. The intrinsic creative ability of artificial intelligence (AI) offers improvements in patient screening, diagnosis, and individualized care. Advanced technologies, like computer vision, machine learning, deep learning, and natural language processing, can analyze large datasets and identify patterns that permit early cancer detection, diagnosis, management and incorporation of conclusive treatment plans, ensuring improved quality of life for patients by personalizing care and minimizing unnecessary interventions. Genomics, transcriptomics and proteomics data can be combined with AI algorithms to unveil an extensive overview of cancer biology, assisting in its detailed understanding and will help in identifying new drug targets and developing effective therapies. This can also help to identify personalized molecular signatures which can facilitate tailored interventions addressing the unique aspects of each patient. AI-driven transcriptomics, proteomics, and genomes represents a revolutionary strategy to improve patient outcome by offering precise diagnosis and tailored therapy. The inclusion of AI in oncology may boost efficiency, reduce errors, and save costs, but it cannot take the role of medical professionals. While clinicians and doctors have the final say in all matters, it might serve as their faithful assistant

Abstract Image

查看原文本刊更多论文

人工智能在癌症早期检测、诊断和量身定制治疗方面的进展和意义

癌症的复杂性和异质性使得早期发现和有效治疗对于提高患者的生存和生活质量至关重要。人工智能（AI）固有的创新能力为患者筛查、诊断和个性化护理提供了改进。计算机视觉、机器学习、深度学习和自然语言处理等先进技术可以分析大型数据集并识别模式，从而实现早期癌症检测、诊断、管理和纳入结结性治疗计划，通过个性化护理和减少不必要的干预，确保提高患者的生活质量。基因组学、转录组学和蛋白质组学数据可以与人工智能算法相结合，揭示癌症生物学的广泛概述，协助其详细理解，并将有助于确定新的药物靶点和开发有效的治疗方法。这也有助于识别个性化的分子特征，从而促进针对每个患者独特方面的量身定制的干预措施。人工智能驱动的转录组学、蛋白质组学和基因组学代表了一种革命性的策略，通过提供精确的诊断和量身定制的治疗来改善患者的预后。将人工智能纳入肿瘤学可能会提高效率，减少错误，节省成本，但它不能扮演医疗专业人员的角色。虽然临床医生和医生在所有问题上都有最终决定权，但它可能会成为他们忠实的助手

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Seminars in oncology 医学-肿瘤学

CiteScore

6.60

自引率

0.00%

发文量

审稿时长

104 days

期刊介绍： Seminars in Oncology brings you current, authoritative, and practical reviews of developments in the etiology, diagnosis and management of cancer. Each issue examines topics of clinical importance, with an emphasis on providing both the basic knowledge needed to better understand a topic as well as evidence-based opinions from leaders in the field. Seminars in Oncology also seeks to be a venue for sharing a diversity of opinions including those that might be considered "outside the box". We welcome a healthy and respectful exchange of opinions and urge you to approach us with your insights as well as suggestions of topics that you deem worthy of coverage. By helping the reader understand the basic biology and the therapy of cancer as they learn the nuances from experts, all in a journal that encourages the exchange of ideas we aim to help move the treatment of cancer forward.