Improved diagnosis of rheumatoid arthritis using an artificial neural network.
Improved diagnosis of rheumatoid arthritis using an artificial neural network.
复制标题
DOI：
10.1038/s41598-022-13750-9
复制
发表时间：
2022-06-13
影响因子：
4.6
通讯作者：
Cui, Liyan
中科院分区：
文献类型：
--
作者：
Bai, Linlu;Zhang, Yuan;Wang, Pan;Zhu, Xiaojun;Xiong, Jing-Wei;Cui, Liyan
类风湿性关节炎（RA）是一种慢性全身性疾病，可导致关节损伤、残疾和破坏性多关节炎.目前RA的诊断是基于临床和实验室特征的结合。然而，由于与其他关节炎的症状重叠，RA在疾病发作时诊断可能很困难，因此早期识别和诊断RA可以更好地管理患者。为了提高RA的医学诊断和评估不同的临床特征对RA诊断的影响，我们采用人工神经网络（ANN）作为训练算法，并使用五重交叉验证来评估其性能。从每个样本中，我们获得了6个特征的数据：年龄、性别、类风湿因子、抗瓜氨酸肽抗体（CCP）、14-3-3η和抗氨甲酰化蛋白（CarP）抗体。训练后，该ANN模型为每个样本分配了一个RA患者或非RA患者的概率。在验证数据集上，该ANN模型对所有样本的F1为0.916，高于我们之前使用最佳阈值算法报告的0.906。因此，该人工神经网络算法不仅提高了RA诊断的准确性，而且还揭示了抗CCP对RA诊断的影响最大，而年龄和抗CarP对RA诊断的影响较弱。
Rheumatoid arthritis (RA) is chronic systemic disease that can cause joint damage, disability and destructive polyarthritis. Current diagnosis of RA is based on a combination of clinical and laboratory features. However, RA diagnosis can be difficult at its disease onset on account of overlapping symptoms with other arthritis, so early recognition and diagnosis of RA permit the better management of patients. In order to improve the medical diagnosis of RA and evaluate the effects of different clinical features on RA diagnosis, we applied an artificial neural network (ANN) as the training algorithm, and used fivefold cross-validation to evaluate its performance. From each sample, we obtained data on 6 features: age, sex, rheumatoid factor, anti-citrullinated peptide antibody (CCP), 14-3-3η, and anti-carbamylated protein (CarP) antibodies. After training, this ANN model assigned each sample a probability for being either an RA patient or a non-RA patient. On the validation dataset, the F1 for all samples by this ANN model was 0.916, which was higher than the 0.906 we previously reported using an optimal threshold algorithm. Therefore, this ANN algorithm not only improved the accuracy of RA diagnosis, but also revealed that anti-CCP had the greatest effect while age and anti-CarP had a weaker on RA diagnosis.
登录
查看更多内容
影响因子：
5.8
作者：
Kursa, Miron B.;Rudnicki, Witold R.
通讯作者：
Rudnicki, Witold R.
影响因子：
4.6
作者：
Fukae, Jun;Isobe, Masato;Koike, Takao
通讯作者：
Koike, Takao
影响因子：
6.2
作者：
Andersen, Jakob Kristian Holm;Pedersen, Jannik Skyttegaard;Just, Soren Andreas
通讯作者：
Just, Soren Andreas
影响因子：
3.4
作者：
Ureten, Kemal;Erbay, Hasan;Maras, Hadi Hakan
通讯作者：
Maras, Hadi Hakan
影响因子：
13.8
作者：
Norgeot, Beau;Glicksberg, Benjamin S.;Butte, Atul J.
通讯作者：
Butte, Atul J.