白鸟 (2025-05-27 15:06):
#paper doi:10.1186/s12859-023-05603-7, A score-based method of immune status evaluation for healthy individuals with complete blood cell counts. 文章介绍了基于16715名健康个体全血细胞计数 (CBC) 的免疫状态评分模型。 主要步骤如下: 1.数据采集:16715 名健康个体的CBC免疫相关的15个免疫指标; 2.数据质控:剔除细菌感染和炎症指标感染的数据; 3.数据归一化:三平台归一化,即log_norm归一化; 4.免疫状态聚类:利用期望最大化(EM-GMM)技术对高斯混合模型优化,聚类,免疫状态分三组,良好/中等/较差; 5.CBC指标与免疫状态的相关性评估:采用 RF、LightGBM 和 XGBoost 算法来评估各CBC指标与免疫状态之间的相关性(权重);权重反映CBC指标与人体免疫状态的相关程度; 6.免疫力评分计算:加权和模型,scores= a1*WBC+a2*NEUT+...+a15*BLR; 7.免疫状态评估:免疫状态曲线(age-score曲线):三阶多项式回归模型; 免疫评分>年龄的拟合值:免疫健康; 免疫评分<年龄的拟合值:免疫状态欠佳或亚健康; 研究意义:健康人的异常免疫状态进行早期预警;
A score-based method of immune status evaluation for healthy individuals with complete blood cell counts
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Abstract:
Abstract Background With the COVID-19 outbreak, an increasing number of individuals are concerned about their health, particularly their immune status. However, as of now, there is no available algorithm that effectively assesses the immune status of normal, healthy individuals. In response to this, a new score-based method is proposed that utilizes complete blood cell counts (CBC) to provide early warning of disease risks, such as COVID-19. Methods First, data on immune-related CBC measurements from 16,715 healthy individuals were collected. Then, a three-platform model was developed to normalize the data, and a Gaussian mixture model was optimized with expectation maximization (EM-GMM) to cluster the immune status of healthy individuals. Based on the results, Random Forest (RF), Light Gradient Boosting Machine (LightGBM) and Extreme Gradient Boosting (XGBoost) were used to determine the correlation of each CBC index with the immune status. Consequently, a weighted sum model was constructed to calculate a continuous immunity score, enabling the evaluation of immune status. Results The results demonstrated a significant negative correlation between the immunity score and the age of healthy individuals, thereby validating the effectiveness of the proposed method. In addition, a nonlinear polynomial regression model was developed to depict this trend. By comparing an individual’s immune status with the reference value corresponding to their age, their immune status can be evaluated. Conclusion In summary, this study has established a novel model for evaluating the immune status of healthy individuals, providing a good approach for early detection of abnormal immune status in healthy individuals. It is helpful in early warning of the risk of infectious diseases and of significant importance.
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