ArticleBMC bioinformatics2023
A score-based method of immune status evaluation for healthy individuals with complete blood cell counts.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Immune status assessment based on plasma proteomics with meta graph convolutional networks.BMC genomics · 2025Article
- Serological insights from SARS-CoV-2 heterologous prime and boost responses in Thailand.Scientific reports · 2025Article
- Machine learning-guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder.Frontiers in psychiatry · 2025Article
- BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.Briefings in bioinformatics · 2024Article
- Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study.PeerJ. Computer science · 2024Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundWith 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.
methodsFirst, 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.
resultsThe 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.
conclusionIn 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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