基于机器学习的医学影像分析在药物研发和精准医疗方面的应用

MRI,PET,和CT等医学影像在新药研发和精准医疗中起着越来越重要的作用。影像技术可以被用来诊断疾病,评估药效,选择适应患者,或者确定用药剂量。 随着人工智能技术的发展,特别是机器学习以及深度学习技术在医学影像中的应用,使得我们可以用更短的时间,更少的放射剂量获取更高质量的影像。这些技术还可以帮助放射科医生缩短读片时间,提高诊断准确率。除此之外,机器学习技术还可以提高量化分析的可行性和精度,帮助建立影像与基因以及疾病的临床表现之间的关系。首先根据不同形态的医学影像,简单介绍他们在药物研发和精准医疗中的应用。并对机器学习在医学影像中的功能作一概括总结。最后讨论这个领域的挑战和机遇。

Machine Learning in Medical Imaging:the Applications in Drug Discovery and Precision Medicine

Medical imaging, such as MRI, PET, and CT, is playing a more and more important role in drug development and precision medicine. It can be used to diagnose disease, evaluate drug effect, select the right patient, or determine the most appropriate drug dose. With the advances in artificial intelligence, especially the extensive applications of machine learning and deep learning in medical imaging, it is possible to use shorter time or less radiation dose to acquire high quality images. AI also help radiologists improve the performance of diagnosis. Moreover, machine learning methods are very useful in quantitative analysis, and gaining insights about the relationship between images, genotypes, and clinical phenotypes. This paper gives an overview of applications of medical imaging in drug development and precision medicine based on the modality of the technologies, as well as how machine learning methods were used in these applications. Challenges and opportunities are discussed in the end.