Convergence of nanotechnology and artificial intelligence in the fight against liver cancer: a comprehensive review.

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Discover. Oncology Pub Date : 2025-01-22 DOI:10.1007/s12672-025-01821-y
Manjusha Bhange, Darshan Telange
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Abstract

Liver cancer is one of the most challenging malignancies, often associated with poor prognosis and limited treatment options. Recent advancements in nanotechnology and artificial intelligence (AI) have opened new frontiers in the fight against this disease. Nanotechnology enables precise, targeted drug delivery, enhancing the efficacy of therapeutics while minimizing off-target effects. Simultaneously, AI contributes to improved diagnostic accuracy, predictive modeling, and the development of personalized treatment strategies. This review explores the convergence of nanotechnology and AI in liver cancer treatment, evaluating current progress, identifying existing research gaps, and discussing future directions. We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring of treatment efficacy, and enhance clinical decision-making. By integrating AI with nanotechnology, clinicians can achieve more accurate patient stratification and treatment personalization, ultimately improving patient outcomes. This convergence holds significant promise for transforming liver cancer therapy into a more precise, individualized, and efficient process. However, data privacy, regulatory hurdles, and the need for large-scale clinical validation remain. Addressing these issues will be essential to fully realizing the potential of these technologies in oncology.

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纳米技术与人工智能在对抗肝癌中的结合:综合综述。
肝癌是最具挑战性的恶性肿瘤之一,通常与预后不良和治疗选择有限有关。纳米技术和人工智能(AI)的最新进展为防治这种疾病开辟了新的领域。纳米技术能够精确、有针对性地给药,提高治疗效果,同时最大限度地减少脱靶效应。同时,人工智能有助于提高诊断准确性、预测建模和制定个性化治疗策略。这篇综述探讨了纳米技术和人工智能在肝癌治疗中的融合,评估了目前的进展,确定了现有的研究差距,并讨论了未来的方向。我们重点介绍了人工智能算法如何优化纳米载体设计,促进治疗效果的实时监测,并增强临床决策。通过将人工智能与纳米技术相结合,临床医生可以实现更准确的患者分层和个性化治疗,最终改善患者的治疗效果。这种融合为肝癌治疗转变为更精确、个性化和高效的过程带来了重大希望。然而,数据隐私、监管障碍和大规模临床验证的需求仍然存在。解决这些问题对于充分发挥这些技术在肿瘤学中的潜力至关重要。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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