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使用机器学习技术进行肺癌治疗的广泛审查:最先进的技术和前景

Shaban Ahmad¹, Khalid Raza¹

¹Department of Computer Science, Jamia Millia Islamia, New Delhi, India.

Journal of drug targeting

|April 25, 2024

概括

人工智能 (AI) 通过分析个人化治疗数据来加速肺癌药物开发. 人工智能模型的准确度超过95%,彻底改变了抗癌疗法,节省了研究人员的时间.

科学领域:

在瘤学瘤学.
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

肺癌每年造成数百万人的死亡,需要快速开发药物.
超过100种类型的人类癌症突出显示,迫切需要创新的治疗策略.
人工智能 (AI) 为开发新型抗癌疗法提供了一个关键的解决方案.

研究的目的:

审查人工智能在开发肺癌疗法中的多样化应用.
探索AI如何优化治疗策略并提高治疗效率.
确定AI在个性化治疗建议和最大限度地减少不良影响中的作用.

主要方法:

一个全面的文献审查的文章索引在PubMed和Scopus.
编译和分析各种机器学习方法,包括CNN,RNN,GAN和VAE.
通过计算机辅助药物设计过程验证人工智能技术.

主要成果:

人工智能模型在分析大数据集以设计药物方面表现出高准确度,超过95%.
预测模型可以根据临床和遗传数据提供个性化治疗建议.
人工智能简化了药物开发,提高了效率,并可能减少不良影响.

结论:

人工智能对肺癌治疗具有变革潜力,可以优化策略并改善结果.
人工智能应用可以显著节省生物科学家在药物发现中的时间和精力.
进一步的研究对于克服挑战和充分实现AI在肺癌治疗方面的能力至关重要.

关键词:

人工智能的人工智能是人工智能.癌症生物学癌症生物学深度学习是一种深度学习.药物设计是药物的设计.肺癌是一种肺癌.机器学习是机器学习.预测建模预测建模

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