机器学习算法在医疗领域中的应用
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摘要
阐述了机器学习的定义及分类,介绍了决策树、贝叶斯网络、人工神经网络、支持向量机、深度学习等经典算法,重点分析了机器学习在疾病预测、疾病辅助诊断、疾病预后评估、新药研发、健康管理、医学图像识别等医疗领域的应用情况,指出了机器学习在医疗领域的应用还可拓展到病案推理、药物警戒等方面,对于进一步提升整个医疗行业的发展意义重大。
The concept and classification of machine learning were described, and the classical algorithms were described such as decision trees, Bayesian network, artificial neural network, support vector machine and deep learning. The application of machine learning was analyzed in the fields of disease prediction, disease auxiliary diagnosis, disease prognosis evaluation,new drug development, health control, medical image recognition and etc. It's pointed out machine learning could be used for medical records inference, pharmacovigilance and etc.
The concept and classification of machine learning were described, and the classical algorithms were described such as decision trees, Bayesian network, artificial neural network, support vector machine and deep learning. The application of machine learning was analyzed in the fields of disease prediction, disease auxiliary diagnosis, disease prognosis evaluation,new drug development, health control, medical image recognition and etc. It's pointed out machine learning could be used for medical records inference, pharmacovigilance and etc.
引文
[1]叶雷.机器学习算法在医疗数据分析中的应用[D].武汉:华中师范大学,2017.
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[11]刘方园,王水花,张煜东.支持向量机模型与应用综述[J]计算机系统应用,2018,27(4):1-9.
[12]LECUN Y,BENGIO Y,HINTO G. Deep learning[J]. Nature,2015,521(7 553):436-444.
[13]张柏雯,林岚,吴水才.深度学习在轻度认知障碍转化与分类中的应用分析[J].医疗卫生装备,2017,38(9):106-107.
[14]机器学习即将彻底颠覆医疗诊断系统[EB/OL].(2017-05-05)[2018-09-05]. http://www.sohu.com/a/138440982_119709.
[15]WENG S F,REPS J,KAI J,et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data?[J]. PLoS One,2017,12(4):e0174944.
[16]MAHESH KUMAR S V,GUNASUN DARI R. Computeraided diagnosis of anterior segment eye abnormalities using visible wavelength image analysis based machine learning[J].J Med Syst,2018,42(7):128.
[17]REHME A K,VOLZ L J,FEIS D L,et al. Identifying neuroimaging markers of motor disability in acute stroke by machine learning techniques[J]. Cereb Cortex,2015,25(9):3 046-3 056.
[18]ASADI H,KOK H K,LOOBY S,et al. Out comes and complications after endovascular treatment of brain arteriovenous malformations:a prognostication attempt using artificial intelligence[J]. World Neurosurg,2016,96:562-569.
[19]HOPE T M,SEGHIER M L,LEFF A P,et al. Predicting outcome and recovery after stroke with lesions extracted from MRI images[J]. Neuroimage Clin,2013,2:424-433.
[20]AI将在这五大方向触发医疗领域的变革[EB/OL].(2016-09-19)[2018-09-05]. http://www.eeworld.com.cn/medical_electronics/article_201609196854.html.
[21]穿戴设备可以通过机器学习发现糖尿病的早期症状[EB/OL].(2018-03-26)[2018-09-05]. https://blog.csdn.net/gS780J/article/details/79706924.
[22]DAVID J,KRISHNAN R,KUMAR A. Neural network based retinal image analysis[C]//2008 Congress on Image and Signal Processing,May 27-30,2008,Sanya,Hainan,China. New York:IEEE,2008,2:49-53.
[23]GOTTLIEB A,STEIN G Y,RUPPIN E,et al. A method for inferring med,diagnoses from patient similarities[J]. BMC Med,2013,11:194.
[24]VILAR S,RYAN P B,MADIGAN D,et al. Similarity-based modeling applied to signal detection in pharmacovigilance[J].CPT Pharmacometrics Syst Pharmacol,2014,3:e137.
[2]DEO R C. Machine learning in medicine[J]. Circulation,2015,132(20):1 920-1 921.
[3]BASTANLAR Y,OZUUSAL M. Introduction to machine learning[J]. Methods Mol Biol,2014,1 107:105-128.
[4]贾青宁,任洪亮,程兴冉.基于决策树的卫生装备数质量预警模型的应用探讨[J].医疗卫生装备,2017,38(12):21-22.
[5]江明尹,刘胜林,程菊,等.基于决策树的医疗器械行业发展分析应用研究[J].医疗卫生装备,2016,37(3):24-25.
[6]VARPA K,ILTANEN K,JUHOLA M. Machine learning method for knowledge discovery experimented with otoneurdigical data[J]. Comput Methods Programs Biomed,2008,91(2):155.
[7]董婕逊.基于贝叶斯网络的银行支付系统动态安全风险评估和最优控制决策[J].信息与电脑(理论版),2018(9):189.
[8]LO Y C,RENSI S E,TORNG W,et al. Machine learning in chemoinformatics and drug discovery[J]. Drug Discov Today,2018,23(8):1 538-1 546.
[9]赵霞. BP神经网络及其在医学领域的应用[J].医疗卫生装备,2010,31(10):43-44.
[10]JIANG F,JIANG Y,ZHI H,et al. Artificial intelligence in healthcare:past,present and future[J]. Stroke Vasc Neurol,2017,2(4):230-243.
[11]刘方园,王水花,张煜东.支持向量机模型与应用综述[J]计算机系统应用,2018,27(4):1-9.
[12]LECUN Y,BENGIO Y,HINTO G. Deep learning[J]. Nature,2015,521(7 553):436-444.
[13]张柏雯,林岚,吴水才.深度学习在轻度认知障碍转化与分类中的应用分析[J].医疗卫生装备,2017,38(9):106-107.
[14]机器学习即将彻底颠覆医疗诊断系统[EB/OL].(2017-05-05)[2018-09-05]. http://www.sohu.com/a/138440982_119709.
[15]WENG S F,REPS J,KAI J,et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data?[J]. PLoS One,2017,12(4):e0174944.
[16]MAHESH KUMAR S V,GUNASUN DARI R. Computeraided diagnosis of anterior segment eye abnormalities using visible wavelength image analysis based machine learning[J].J Med Syst,2018,42(7):128.
[17]REHME A K,VOLZ L J,FEIS D L,et al. Identifying neuroimaging markers of motor disability in acute stroke by machine learning techniques[J]. Cereb Cortex,2015,25(9):3 046-3 056.
[18]ASADI H,KOK H K,LOOBY S,et al. Out comes and complications after endovascular treatment of brain arteriovenous malformations:a prognostication attempt using artificial intelligence[J]. World Neurosurg,2016,96:562-569.
[19]HOPE T M,SEGHIER M L,LEFF A P,et al. Predicting outcome and recovery after stroke with lesions extracted from MRI images[J]. Neuroimage Clin,2013,2:424-433.
[20]AI将在这五大方向触发医疗领域的变革[EB/OL].(2016-09-19)[2018-09-05]. http://www.eeworld.com.cn/medical_electronics/article_201609196854.html.
[21]穿戴设备可以通过机器学习发现糖尿病的早期症状[EB/OL].(2018-03-26)[2018-09-05]. https://blog.csdn.net/gS780J/article/details/79706924.
[22]DAVID J,KRISHNAN R,KUMAR A. Neural network based retinal image analysis[C]//2008 Congress on Image and Signal Processing,May 27-30,2008,Sanya,Hainan,China. New York:IEEE,2008,2:49-53.
[23]GOTTLIEB A,STEIN G Y,RUPPIN E,et al. A method for inferring med,diagnoses from patient similarities[J]. BMC Med,2013,11:194.
[24]VILAR S,RYAN P B,MADIGAN D,et al. Similarity-based modeling applied to signal detection in pharmacovigilance[J].CPT Pharmacometrics Syst Pharmacol,2014,3:e137.