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肿瘤学中的人工智能进展:当前趋势与未来方向综述

Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions.

作者信息

Huhulea Ellen N, Huang Lillian, Eng Shirley, Sumawi Bushra, Huang Audrey, Aifuwa Esewi, Hirani Rahim, Tiwari Raj K, Etienne Mill

机构信息

School of Medicine, New York Medical College, Valhalla, NY 10595, USA.

Barshop Institute, The University of Texas Health Science Center, San Antonio, TX 78229, USA.

出版信息

Biomedicines. 2025 Apr 13;13(4):951. doi: 10.3390/biomedicines13040951.

Abstract

Cancer remains one of the leading causes of mortality worldwide, driving the need for innovative approaches in research and treatment. Artificial intelligence (AI) has emerged as a powerful tool in oncology, with the potential to revolutionize cancer diagnosis, treatment, and management. This paper reviews recent advancements in AI applications within cancer research, focusing on early detection through computer-aided diagnosis, personalized treatment strategies, and drug discovery. We survey AI-enhanced diagnostic applications and explore AI techniques such as deep learning, as well as the integration of AI with nanomedicine and immunotherapy for cancer care. Comparative analyses of AI-based models versus traditional diagnostic methods are presented, highlighting AI's superior potential. Additionally, we discuss the importance of integrating social determinants of health to optimize cancer care. Despite these advancements, challenges such as data quality, algorithmic biases, and clinical validation remain, limiting widespread adoption. The review concludes with a discussion of the future directions of AI in oncology, emphasizing its potential to reshape cancer care by enhancing diagnosis, personalizing treatments and targeted therapies, and ultimately improving patient outcomes.

摘要

癌症仍然是全球主要的死亡原因之一,这推动了在研究和治疗方面采用创新方法的需求。人工智能(AI)已成为肿瘤学领域的强大工具,有潜力彻底改变癌症的诊断、治疗和管理方式。本文综述了癌症研究中人工智能应用的最新进展,重点关注通过计算机辅助诊断进行早期检测、个性化治疗策略以及药物发现。我们调查了人工智能增强的诊断应用,并探索了深度学习等人工智能技术,以及人工智能与纳米医学和免疫疗法在癌症治疗中的整合。文中呈现了基于人工智能的模型与传统诊断方法的对比分析,凸显了人工智能的卓越潜力。此外,我们讨论了整合健康的社会决定因素以优化癌症治疗的重要性。尽管有这些进展,但数据质量、算法偏差和临床验证等挑战依然存在,限制了其广泛应用。综述最后讨论了人工智能在肿瘤学中的未来发展方向,强调其通过加强诊断、个性化治疗和靶向治疗最终改善患者预后从而重塑癌症治疗的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caca/12025054/6256aa87e37b/biomedicines-13-00951-g001.jpg

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