ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveTo evaluate the clinical efficacy and economic value of the Jiangsu Traditional Chinese Medicine （TCM） Diagnosis and Treatment Protocol for Dominant Diseases （abbreviated as the Diagnosis and Treatment Protocol） in adult patients with non-severe community-acquired pneumonia （CAP） based on real-world clinical data. MethodsA retrospective real-world cohort study was conducted using electronic medical records of adult patients hospitalized for non-severe CAP from September 1st， 2023 to December 31st， 2024 across 10 TCM hospitals in Jiangsu province. Patients were classified into an exposure group and a non-exposure group based on whether they received Chinese herbal medicine （CHM） according to the Diagnosis and Treatment Protocol. The non-exposure group received only conventional western medicine， while the exposure group additionally received differentiated CHM for at least five consecutive days. Outcomes were compared between two patient groups， including cough resolution rate， sputum resolution rate （assessed by volume， color， and consistency）， incidence of abnormal C-reactive protein （CRP）， incidence of abnormal white blood cell （WBC） count， and radiographic resolution rate of pulmonary infiltrates on chest imaging. Multivariable logistic regression was performed to identify factors influencing clinical efficacy. Subgroup analyses were conducted according to age， gender， smoking status， history of hypertension， and pneumonia severity score （CURB-65）， and the efficacy of treatment for cough and sputum was analyzed within each subgroup. Cost-effectiveness analysis was conducted using cough resolution rate as the outcome measure， evaluating the pharmacoeconomics of the two groups. ResultsA total of 1688 patients were included with 1293 in the exposure group and 395 in the non-exposure group. Compared to the non-exposure group， the exposure group demonstrated significantly higher resolution rates of cough， sputum volume， color， and consistency， as well as a significantly lower incidence of abnormal CRP （P＜0.05）. No statistically significant difference was observed between the groups in terms of abnormal WBC count and radiographic resolution rate of pulmonary infiltrates （P＞0.05）. Logistic regression analysis showed that the cough resolution rate in the exposure group was 1.83 times that of the non-exposure group， while the probabilities of resolution in sputum volume， color， and consistency were 1.37， 2.09， and 1.56 times those of the non-exposure group， respectively （P＜0.05）. Subgroup analyses showed that the exposure group achieved significantly higher cough resolution rates across most subgroups except for populations with a CURB-65 score ≥2 or those with a history of hypertension （P＜0.05）. Specifically， among females， patients aged ≥18 and ＜65 years， non-smokers， those without hypertension， and those with a CURB-65 score of 0， the exposure group showed a higher cough resolution rate than the non-exposure group （P＜0.05）. From an economic perspective， total hospitalization cost， length of stay， antibiotic cost， and CHM cost all differed significantly between groups （P＜0.05）. The cost-effectiveness ratio （CER） was 10,788.80 CNY/case in the exposure group， while 22,513.80 CNY/case in the non-exposure group. This implies that， compared with the exposure group， the non-exposure group incurred an additional 17,302.27 CNY to achieve one case of cough resolution. When the willingness-to-pay threshold ranged from 0 to 50,000 CNY， the probability of economic advantage was consistently higher in the exposure group than in the non-exposure group. ConclusionOn the basis of conventional western medicine， the addition of CHM in accordance with the Diagnosis and Treatment Protocol can effectively improve clinical symptoms， reduce inflammatory markers， promote clinical recovery， and is more cost-effective in treating adults with non-severe CAP.

ObjectiveTo observe the real‑world effectiveness and economic outcomes of Weishi Qingjin Formula （苇石清金方， WQF） in the treatment of adult community‑acquired pneumonia （CAP） with phlegm‑heat obstructing the lung syndrome. MethodsBased on a multicenter， real-world retrospective cohort study， clinical data were collected from hospitalized adult patients diagnosed with non‑severe CAP and phlegm‑heat obstructing the lung syndrome in 10 traditional Chinese medicine （TCM） hospitals in Jiangsu province. Patients were divided into an exposure group （those who received oral WQF） and a non‑exposure group （those who did not）. The following outcomes were compared between the two groups before and after treatment， which were remission rates of clinical symptoms including cough， expectoration （sputum volume， color， consistency）， and chest pain， levels of inflammatory markers including C‑reactive protein （CRP） and white blood cell count （WBC）， and the rate of pulmonary inflammatory absorption on chest CT. Subgroup analyses were performed based on age， gender， smoking status， presence of hypertension， and the severity of community-acquired pneumonia （CURB‑65） score， comparing the two groups in terms of cough remission rate， chest pain remission rate， and chest CT absorption rate. For health economic evaluation， cost‑effectiveness analysis was used to calculate the cost‑effectiveness ratio （CER） and incremental cost‑effectiveness ratio （ICER）. Univariate sensitivity analysis and probabilistic sensitivity analysis were performed to test the robustness of the results. ResultsA total of 647 patients in the exposure group and 1491 patients in the non-exposure group were included in the final statistical analysis. There was no statistically significant difference in length of hospital stay， gender， marital status， smoking history， bronchoscopy history， and comorbidities between the groups （P＞0.05）， but age， CURB-65 score， and antibiotic use. The exposure group had significantly higher remission rates of cough and sputum consistency than the non-exposure group （P＜0.05）. After adjusting for confounders using propensity score matching and logistic regression， the cough remission rate in the exposure group was 1.49 times that of the non-exposure group （P＜0.01）. No significant difference was observed between groups in the reduction rates of CRP and WBC， and in the rate of pulmonary inflammatory absorption on chest CT （P＞0.05）. Subgroup analyses revealed that the cough remission rate in the exposure group was significantly better than that in the non-exposure group except for patients aged ≥65 years， smokers， hypertensive patients， those using other type antibiotics or not using antibiotics， and those with a CURB-65 score ≥1 （P＜0.05）. Among smokers， the chest pain remission rate in the exposure group was 4.38 times that of the non-exposure group （P＜0.01）. No significant difference in chest CT absorption rate was found between groups across subgroups of gender， age， hypertension status， or antibiotic type （P＞0.05）. In terms of economic evaluation， CER was 10,877.60 CNY/case in the exposure group and 16,773.10 CNY/case in the non-exposure group. Compared to the exposure group， the non-exposure group incurred an additional 15,034.26 CNY to achieve one case of cough resolution， indicating a more favorable cost-effectiveness profile. Probabilistic sensitivity analysis yielded results consistent with the cost-effectiveness analysis， confirming the robustness of the findings. ConclusionWQF demonstrates significant efficacy in improving cough symptoms in the treatment of adult CAP with phlegm-heat obstructing the lung syndrome， and also exhibits favorable economic benefits.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveTo evaluate the clinical efficacy and economic value of the Jiangsu Traditional Chinese Medicine （TCM） Diagnosis and Treatment Protocol for Dominant Diseases （abbreviated as the Diagnosis and Treatment Protocol） in adult patients with non-severe community-acquired pneumonia （CAP） based on real-world clinical data. MethodsA retrospective real-world cohort study was conducted using electronic medical records of adult patients hospitalized for non-severe CAP from September 1st， 2023 to December 31st， 2024 across 10 TCM hospitals in Jiangsu province. Patients were classified into an exposure group and a non-exposure group based on whether they received Chinese herbal medicine （CHM） according to the Diagnosis and Treatment Protocol. The non-exposure group received only conventional western medicine， while the exposure group additionally received differentiated CHM for at least five consecutive days. Outcomes were compared between two patient groups， including cough resolution rate， sputum resolution rate （assessed by volume， color， and consistency）， incidence of abnormal C-reactive protein （CRP）， incidence of abnormal white blood cell （WBC） count， and radiographic resolution rate of pulmonary infiltrates on chest imaging. Multivariable logistic regression was performed to identify factors influencing clinical efficacy. Subgroup analyses were conducted according to age， gender， smoking status， history of hypertension， and pneumonia severity score （CURB-65）， and the efficacy of treatment for cough and sputum was analyzed within each subgroup. Cost-effectiveness analysis was conducted using cough resolution rate as the outcome measure， evaluating the pharmacoeconomics of the two groups. ResultsA total of 1688 patients were included with 1293 in the exposure group and 395 in the non-exposure group. Compared to the non-exposure group， the exposure group demonstrated significantly higher resolution rates of cough， sputum volume， color， and consistency， as well as a significantly lower incidence of abnormal CRP （P＜0.05）. No statistically significant difference was observed between the groups in terms of abnormal WBC count and radiographic resolution rate of pulmonary infiltrates （P＞0.05）. Logistic regression analysis showed that the cough resolution rate in the exposure group was 1.83 times that of the non-exposure group， while the probabilities of resolution in sputum volume， color， and consistency were 1.37， 2.09， and 1.56 times those of the non-exposure group， respectively （P＜0.05）. Subgroup analyses showed that the exposure group achieved significantly higher cough resolution rates across most subgroups except for populations with a CURB-65 score ≥2 or those with a history of hypertension （P＜0.05）. Specifically， among females， patients aged ≥18 and ＜65 years， non-smokers， those without hypertension， and those with a CURB-65 score of 0， the exposure group showed a higher cough resolution rate than the non-exposure group （P＜0.05）. From an economic perspective， total hospitalization cost， length of stay， antibiotic cost， and CHM cost all differed significantly between groups （P＜0.05）. The cost-effectiveness ratio （CER） was 10,788.80 CNY/case in the exposure group， while 22,513.80 CNY/case in the non-exposure group. This implies that， compared with the exposure group， the non-exposure group incurred an additional 17,302.27 CNY to achieve one case of cough resolution. When the willingness-to-pay threshold ranged from 0 to 50,000 CNY， the probability of economic advantage was consistently higher in the exposure group than in the non-exposure group. ConclusionOn the basis of conventional western medicine， the addition of CHM in accordance with the Diagnosis and Treatment Protocol can effectively improve clinical symptoms， reduce inflammatory markers， promote clinical recovery， and is more cost-effective in treating adults with non-severe CAP.

ObjectiveTo observe the real‑world effectiveness and economic outcomes of Weishi Qingjin Formula （苇石清金方， WQF） in the treatment of adult community‑acquired pneumonia （CAP） with phlegm‑heat obstructing the lung syndrome. MethodsBased on a multicenter， real-world retrospective cohort study， clinical data were collected from hospitalized adult patients diagnosed with non‑severe CAP and phlegm‑heat obstructing the lung syndrome in 10 traditional Chinese medicine （TCM） hospitals in Jiangsu province. Patients were divided into an exposure group （those who received oral WQF） and a non‑exposure group （those who did not）. The following outcomes were compared between the two groups before and after treatment， which were remission rates of clinical symptoms including cough， expectoration （sputum volume， color， consistency）， and chest pain， levels of inflammatory markers including C‑reactive protein （CRP） and white blood cell count （WBC）， and the rate of pulmonary inflammatory absorption on chest CT. Subgroup analyses were performed based on age， gender， smoking status， presence of hypertension， and the severity of community-acquired pneumonia （CURB‑65） score， comparing the two groups in terms of cough remission rate， chest pain remission rate， and chest CT absorption rate. For health economic evaluation， cost‑effectiveness analysis was used to calculate the cost‑effectiveness ratio （CER） and incremental cost‑effectiveness ratio （ICER）. Univariate sensitivity analysis and probabilistic sensitivity analysis were performed to test the robustness of the results. ResultsA total of 647 patients in the exposure group and 1491 patients in the non-exposure group were included in the final statistical analysis. There was no statistically significant difference in length of hospital stay， gender， marital status， smoking history， bronchoscopy history， and comorbidities between the groups （P＞0.05）， but age， CURB-65 score， and antibiotic use. The exposure group had significantly higher remission rates of cough and sputum consistency than the non-exposure group （P＜0.05）. After adjusting for confounders using propensity score matching and logistic regression， the cough remission rate in the exposure group was 1.49 times that of the non-exposure group （P＜0.01）. No significant difference was observed between groups in the reduction rates of CRP and WBC， and in the rate of pulmonary inflammatory absorption on chest CT （P＞0.05）. Subgroup analyses revealed that the cough remission rate in the exposure group was significantly better than that in the non-exposure group except for patients aged ≥65 years， smokers， hypertensive patients， those using other type antibiotics or not using antibiotics， and those with a CURB-65 score ≥1 （P＜0.05）. Among smokers， the chest pain remission rate in the exposure group was 4.38 times that of the non-exposure group （P＜0.01）. No significant difference in chest CT absorption rate was found between groups across subgroups of gender， age， hypertension status， or antibiotic type （P＞0.05）. In terms of economic evaluation， CER was 10,877.60 CNY/case in the exposure group and 16,773.10 CNY/case in the non-exposure group. Compared to the exposure group， the non-exposure group incurred an additional 15,034.26 CNY to achieve one case of cough resolution， indicating a more favorable cost-effectiveness profile. Probabilistic sensitivity analysis yielded results consistent with the cost-effectiveness analysis， confirming the robustness of the findings. ConclusionWQF demonstrates significant efficacy in improving cough symptoms in the treatment of adult CAP with phlegm-heat obstructing the lung syndrome， and also exhibits favorable economic benefits.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.