人工智能在乳腺癌管理中的应用综述

Harshita Gandhi, Kapil Kumar
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引用次数: 0

摘要

乳腺癌是一个严重的全球健康问题,早期发现、准确诊断和个性化治疗是改善患者预后的关键。近年来,人工智能(AI)和机器学习(ML)已成为有前途的乳腺癌研究和临床实践工具。使用人工智能和机器学习的早期检测、诊断、预后、药物发现、高级图像分析、精准医学、预测建模和个性化治疗计划等项目正在进行中。这些项目使用不同的算法,包括卷积神经网络(cnn)、支持向量机(svm)、决策树和深度学习方法,来分析和改进不同类型的数据,如乳腺癌管理的临床、基因组和成像数据。这些项目的成功有可能改变乳腺癌的治疗,在这一领域的持续研究和发展可能会导致更准确和个性化的乳腺癌诊断、治疗和结果。
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Artificial Intelligence for the Management of Breast Cancer: An Overview.

Breast cancer is a severe global health problem, and early detection, accurate diagnosis, and personalized treatment is the key to improving patient outcomes. Artificial intelligence (AI) and machine learning (ML) have emerged as promising breast cancer research and clinical practice tools in recent years. Various projects are underway in early detection, diagnosis, prognosis, drug discovery, advanced image analysis, precision medicine, predictive modeling, and personalized treatment planning using artificial intelligence and machine learning. These projects use different algorithms, including convolutional neural networks (CNNs), support vector machines (SVMs), decision trees, and deep learning methods, to analyze and improve different types of data, such as clinical, genomic, and imaging data for breast cancer management. The success of these projects has the potential to transform breast cancer care, and continued research and development in this area is likely to lead to more accurate and personalized breast cancer diagnosis, treatment, and outcomes.

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