A neural network for the molecular discrimination of pulmonary arterial hypertension (PAH) and pulmonary veno-occlusive disease (PVOD)

This feed-forward neural network for discriminating PAH from PVOD is based on the R packages 'caret' and 'nnet'. It was trained on transcriptomics data acquired with the NanoString nCounter technology. Please see the referenced article for further information! The .rds file contains the serialized model. In order to read the model into an R environment the following steps have to be performed: - Start an R terminal - Execute the 'readRDS' function with the (relative) path to the RDS file as only option and store the returned object in a variable - The returned object is of the class caret::train and can directly be used for the classification of samples (given that the data has been identically prepared/normalized) Please see the manuals of the R packages 'caret' and 'nnet' for help on how to use the loaded objects. Examplary R commands: model.caret用于区分肺动脉高压（Pulmonary Arterial Hypertension, PAH）与肺静脉闭塞性疾病（Pulmonary Venous Occlusive Disease, PVOD）的前馈神经网络，基于R语言扩展包'caret'与'nnet'构建。该模型依托NanoString nCounter技术获取的转录组学数据完成训练。如需获取更多详细信息，请参阅所引用的研究论文。该.rds格式文件包含序列化后的模型对象。若要将该模型加载至R运行环境，请执行以下步骤： - 启动R终端 - 以RDS文件的（相对）路径作为唯一参数，执行'readRDS'函数，并将返回的对象存储至变量中 - 返回的对象为caret::train类，可直接用于样本分类（前提是输入数据已完成与训练集一致的预处理与标准化操作） 如需了解如何使用加载后的模型对象，请参阅R扩展包'caret'与'nnet'的官方手册。示例R命令：model.caret