Background: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy.Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with comorbid migraine.Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions.Results: AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), have become instrumental in the discovery of genetic and molecular biomarkers of cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in comorbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments.Conclusions: AI holds significant potential to improve the precision and effectiveness of the management and therapy of cancer patients with comorbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for the approach outlined herein.
背景：癌症仍是全球范围内主要的死亡原因之一。由于个性化治疗面临挑战，尤其是在合并其他疾病的患者中，其有效治疗进展受到阻碍。将人工智能（AI）整合到患者特征分析中，为增强个体化抗癌治疗提供了一种前景广阔的方法。 目的：本文通过叙述性综述探讨了AI在通过个性化特征分析优化抗癌治疗中的作用，特别关注合并偏头痛的癌症患者。 方法：在多个数据库（包括PubMed、Scopus和Google Scholar）中进行了全面的文献检索。研究筛选基于其与AI在肿瘤学和偏头痛管理中的应用相关性，重点关注个性化医疗和预测建模。通过综合关键主题，概述了最新进展、挑战及新兴方向。 结果：机器学习（ML）、深度学习（DL）和自然语言处理（NLP）等AI技术已成为发现癌症和偏头痛遗传与分子生物标志物的重要工具。这些技术还能通过预测分析评估合并症中偏头痛对癌症治疗的影响、预测治疗结果，并提供临床决策支持系统（CDSS）以实现实时治疗调整。 结论：AI在提高合并偏头痛的癌症患者管理及治疗的精准性和有效性方面具有显著潜力。然而，数据整合、临床验证和伦理考量等方面仍存在挑战，必须解决这些问题才能充分发挥本文所述方法的潜力。
AI-Guided Cancer Therapy for Patients with Coexisting Migraines
肿瘤(癌症)患者之家