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基于人工智能的干性指数在癌症中的应用。

Application of artificial intelligence-based stemness index in cancer.

作者信息

Liu Liyuan, Pei Qin, Qadir Javeria, Chen Yiyu, Li Jingyuan, Luo Yanan, Xian Jiawen, Du Rongrong, Ye Ting

机构信息

Department of Laboratory Medicine, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.

Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan.

出版信息

Front Oncol. 2025 Aug 13;15:1608712. doi: 10.3389/fonc.2025.1608712. eCollection 2025.

Abstract

Cancer stem cells (CSCs) exhibit self-renewal and multidirectional differentiation capacities. The stemness of CSCs is the fundamental cause of tumor progression and treatment resistance. The stemness index, evaluating the number and activity of CSCs, is a crucial indicator predicting various aspects of tumor behavior such as growth, metastasis, and prognosis. With the advancements in artificial intelligence (AI), particularly in data analysis and machine learning, the identification and understanding of CSCs' stemness characteristics have improved. The AI-based analysis allows for processing vast datasets and recognizing patterns that assist in comprehending the role of CSCs in cancer development. The utilization of AI to analyze and compute the stemness index holds significant clinical relevance in tumor diagnosis and treatment. This approach provides more precise and personalized information, potentially influencing treatment strategies. Therefore, tailoring treatments specifically targeting CSCs is highly imperative and may enhance therapeutic efficacy and outcomes in cancer patients.

摘要

癌症干细胞(CSCs)具有自我更新和多向分化能力。CSCs的干性是肿瘤进展和治疗耐药的根本原因。评估CSCs数量和活性的干性指数是预测肿瘤行为各个方面(如生长、转移和预后)的关键指标。随着人工智能(AI)的进步,特别是在数据分析和机器学习方面,对CSCs干性特征的识别和理解有了改善。基于AI的分析能够处理大量数据集并识别有助于理解CSCs在癌症发展中作用的模式。利用AI分析和计算干性指数在肿瘤诊断和治疗中具有重要的临床意义。这种方法提供了更精确和个性化的信息,可能会影响治疗策略。因此,量身定制专门针对CSCs的治疗方法至关重要,可能会提高癌症患者的治疗效果和预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9855/12380755/b70fed16cf17/fonc-15-1608712-g001.jpg

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