Applying machine learning to predict patient-specific current CD4 cell count in order to determine the progression of human immunodeficiency virus (HIV) infection

Yashik Singh; Nitesh Narsai; Maurice Mars

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Applying machine learning to predict patient-specific current CD4 cell count in order to determine the progression of human immunodeficiency virus (HIV) infection

机译：应用机器学习预测患者当前的特定CD4细胞计数，以确定人类免疫缺陷病毒（HIV）感染的进程

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This work shows the application of machine learning to predict current CD4?cell count of an HIV-positive patient using genome sequences, viral load and time. A regression model predicting actual CD4?cell counts and a classification model predicting if a patient’s CD4?cell count is less than 200 was built using a support vector machine and neural network. The most accurate regression and classification model took as input the viral load, time, and genome and produced a correlation of co-efficient of 0.9 and an accuracy of 95%, respectively, proving that a CD4?cell count measure may be accurately predicted using machine learning on genotype, viral load and time.

机译：这项工作展示了机器学习在利用基因组序列，病毒载量和时间来预测HIV阳性患者当前CD4？细胞计数中的应用。使用支持向量机和神经网络建立了一个预测模型，该模型可以预测实际的CD4？细胞数量，而一个分类模型可以预测患者的CD4？细胞数量是否小于200。最准确的回归和分类模型将病毒载量，时间和基因组作为输入，并分别产生了0.9的系数和95％的准确度的相关性，证明CD4？细胞计数测量可以使用关于基因型，病毒载量和时间的机器学习。

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《African Journal of Biotechnology》 |2013年第23期|共7页
作者
Yashik Singh; Nitesh Narsai; Maurice Mars;
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中图分类生物工程学（生物技术）;
关键词
Human immunodeficiency virus (HIV)antigensCD4computational biologyartificial intelligencedata miningpattern recognition;

机译：人类免疫缺陷病毒（HIV）抗原CD4计算生物学人工智能数据挖掘模式识别;

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1. Lowest ever CD4 lymphocyte count (CD4 nadir) as a predictor of current cognitive and neurological status in human immunodeficiency virus type 1 infection--The Hawaii Aging with HIV Cohort. [J] . Valcour V, Yee P, Williams AE, Journal of neurovirology . 2006,第5期

机译：有史以来最低的CD4淋巴细胞计数（CD4最低点）可预测人类免疫缺陷病毒1型感染的当前认知和神经系统状况-HIV人群的夏威夷老龄化。
2. Relationships among the detection of p24 antigen, human immunodeficiency virus (HIV) RNA level, CD4 cell count, and disease progression in HIV-infected individuals with hemophilia. [J] . Sabin CA, Lepri AC, Devereux H, The Journal of Infectious Diseases . 2001,第4期

机译：在感染了血友病的HIV感染者中，p24抗原的检测，人类免疫缺陷病毒（HIV）RNA水平，CD4细胞计数与疾病进展之间的关系。
3. Human T cell lymphotropic virus type 1 (HTLV-1) infection increases the CD4 count in human immunodeficiency virus type 1 (HIV-1) infected patients submitted to antiretroviral therapy (ARV) [J] . Filipe FA Rego, Luiz CJ Alcantara, Tulio de Oliveira Retrovirology . 2014,第S1期

机译：人类T细胞1型淋巴病毒（HTLV-1）感染增加了接受抗逆转录病毒疗法（ARV）的人类1型免疫缺陷病毒（HIV-1）感染患者的CD4计数
4. Correlation between total lymphocyte counts and CD4 among human immunodeficiency virus (HIV) patients [C] . I M S Darmana, N W Rusni, S Masyeni Applied Sciences and Engineering Conference . 2018

机译：人免疫缺陷病毒（HIV）患者总淋巴细胞计数和CD4之间的相关性
5. The role of the transmembrane and cytoplasmic domains of the VPU protein of human immunodeficiency virus type 1 (HIV-1) in the acute CD4+ T cell loss and disease in the simian human immunodeficiency virus (SHIV)/macaque model. [D] . Hout, David Richard. 2006

机译：人类免疫缺陷病毒1型（HIV-1）的VPU蛋白的跨膜和胞质域在猿猴人类免疫缺陷病毒（SHIV）/猕猴模型的急性CD4 + T细胞丧失和疾病中的作用。
6. Natural Killer Cell Function Is Well Preserved in Asymptomatic Human Immunodeficiency Virus Type 2 (HIV-2) Infection but Similar to That of HIV-1 Infection When CD4 T-Cell Counts Fall [O] . Samuel Victor Nuvor, Marianne van der Sande, Sarah Rowland-Jones, 2006

机译：在无症状的人类免疫缺陷病毒2型（HIV-2）感染中自然杀伤细胞的功能得到了很好的保留但是当CD4 T细胞计数下降时与HIV-1感染相似。
7. Natural killer cell function is well preserved in asymptomatic human immunodeficiency virus type 2 (HIV-2) infection but similar to that of HIV-1 infection when CD4 T-cell counts fall. [O] . Nuvor, SV, van der Sande, M, Rowland-Jones, S, 2006

机译：在无症状的2型人类免疫缺陷病毒（HIV-2）感染中，自然杀伤细胞的功能得到了很好的保留，但是当CD4 T细胞计数下降时，与HIV-1感染相似。
8. Low Prevalence of Human Immunodeficiency Virus-1 (HIV-1), HIV-2, and Human T CellLymphotropic Virus-1 Infection in Somalia [R] . Scott, D. A., Corwin, A. L., Constantine, N. T., 1991

机译：索马里人类免疫缺陷病毒-1（HIV-1），HIV-2和人类T细胞淋巴细胞病毒-1感染的低患病率

Applying machine learning to predict patient-specific current CD4 cell count in order to determine the progression of human immunodeficiency virus (HIV) infection

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