Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.

Objective:To explore the health economic evaluation methods of disease screening,providing insights for scholars conducting related research.Methods:By integrating relevant content from modem epidemiology,health statistics,and health economics,it investigates the differences in conducting health economic evaluations of disease screening using authenticity indicators(sensitivity,specificity)and predictive value indicators(positive predictive value,negative predictive value),and combines empirical studies with cases from the literature.Results:Authenticity indicators(sensitivity,specificity)are intrinsic measures of diagnostic tests,unaffected by the disease prevalence in the sample population,making them more suitable for conducting health economic evaluations of disease screening.Moreover,authenticity indicators are easy to obtain,and the model calculations are straightforward and convenient.Case study results demonstrate that compared to risk score screening,the Incremental Cost-Effectiveness Ratio(ICER)of fasting plasma glucose(FPG)testing for type 2 diabetes is 626,indicating that for every additional diabetic patient identified through risk score screening,an extra 626 yuan is spent.Conclusion:It is recommended to use authenticity indicators for conducting health economic evaluations of disease screening,standardize the path methods for model selection,and continuously improve the evidence quality of health economic evaluations of disease screening in China.