With the rapid advancement of artificial intelligence technology, chatbots have shown great potential in the healthcare sector. From personalized health advice to chronic disease management and psychological support, chatbots have demonstrated significant advantages in improving the efficiency and quality of healthcare services. As the scope of their applications expands, the relationship between technological complexity and practical application scenarios has become increasingly intertwined, necessitating a more comprehensive evaluation of both aspects. This paper, from the perspective of he althcare applications, systematically reviews the technological pathways and development of chatbots in the medical field, providing an in-depth analysis of their performance across various medical scenarios. It thoroughly examines the advantages and limitations of chatbots, aiming to offer theoretical support for future research and propose feasible recommendations for the broader adoption of chatbot technologies in healthcare.

Objective To investigate the incidence of placental abruption in the third trimester of pregnancy in Hebei Province,identify its associated risk factors,and develop a corresponding nomogram prediction model.Methods Data from pregnant women at 22 monitored hospitals in Hebei Province,collected between 2013 and 2023,were analyzed to assess the incidence,trends,and associated risk factors of placental abruption.A prediction model was developed and visualized using R programming to generate the receiver operating characteristic(ROC)curve.The model's predictive performance was evaluated using the area under the curve(AUC)and calibration curve parameters.Results A total of 480 690 pregnant women were included in this study over the specified period.The incidence of placental abruption was 0.29%(1 395 out of 480 690),with an average annual percentage change of 2.73%,indicating a stable trend(P=0.34).Multivariate logistic regression analysis revealed that pregnancy-related anemia,preeclampsia,placenta previa,vaginal bleeding before 28 weeks'gestation,and between 28 and 31+6 weeks'gestation were significant risk factors for placental abruption(all P<0.05).In contrast,regular prenatal examinations(7～11 visits)and multiple pregnancies were identified as protective factors against placental abruption(both P<0.05).The area under the curve(AUC)for the nomogram model constructed based on independent risk factors for placental abruption was 0.79,and the calibration curve demonstrated that the predicted values closely aligned with the observed values.Conclusions Prenatal examinations should be prioritized,especially for women with preeclampsia,placenta previa,or a history of vaginal bleeding before 28 weeks of gesta-tion.Management of pregnancies between 28 and 31+6 weeks is also crucial to reduce the incidence of placental abruption and mitigate adverse maternal and neonatal outcomes.The nomogram model constructed based on these factors exhibits excellent predictive performance,providing a solid theoretical foundation for the prevention and clinical management of placental abruption.

Objective To investigate the incidence of placental abruption in the third trimester of pregnancy in Hebei Province,identify its associated risk factors,and develop a corresponding nomogram prediction model.Methods Data from pregnant women at 22 monitored hospitals in Hebei Province,collected between 2013 and 2023,were analyzed to assess the incidence,trends,and associated risk factors of placental abruption.A prediction model was developed and visualized using R programming to generate the receiver operating characteristic(ROC)curve.The model's predictive performance was evaluated using the area under the curve(AUC)and calibration curve parameters.Results A total of 480 690 pregnant women were included in this study over the specified period.The incidence of placental abruption was 0.29%(1 395 out of 480 690),with an average annual percentage change of 2.73%,indicating a stable trend(P=0.34).Multivariate logistic regression analysis revealed that pregnancy-related anemia,preeclampsia,placenta previa,vaginal bleeding before 28 weeks'gestation,and between 28 and 31+6 weeks'gestation were significant risk factors for placental abruption(all P<0.05).In contrast,regular prenatal examinations(7～11 visits)and multiple pregnancies were identified as protective factors against placental abruption(both P<0.05).The area under the curve(AUC)for the nomogram model constructed based on independent risk factors for placental abruption was 0.79,and the calibration curve demonstrated that the predicted values closely aligned with the observed values.Conclusions Prenatal examinations should be prioritized,especially for women with preeclampsia,placenta previa,or a history of vaginal bleeding before 28 weeks of gesta-tion.Management of pregnancies between 28 and 31+6 weeks is also crucial to reduce the incidence of placental abruption and mitigate adverse maternal and neonatal outcomes.The nomogram model constructed based on these factors exhibits excellent predictive performance,providing a solid theoretical foundation for the prevention and clinical management of placental abruption.

Objective:The study aimed to quantify the contents of peimine and peiminine in huangshi xiangsheng pills using a nano quantity analyte detector(NQAD)and compare the results with the evaporative light scattering detector(ELSD).Methods:Analytical separation was conducted utilizing a CAPCELL PAK MG Ⅲ C18 column(4.6 mm ×250 mm,5 μmi)as the stationary phase.The mobile phase consisted of a mixture of acetonitrile-water-diethylamine(65∶35∶0.03),with a flow rate set at 1.0 mL·min-1 and the column maintained at a temperature of 25℃.Results:NQAD analysis revealed a robust linear correlation between the concentration and the peak area for peimine within a concentration range of 2.450 to 1.470 μg·mL-1,achieving a correlation coefficient of 0.999 3.The limit of detection(LOD)and recovery rate for peimine were determined to be 14.70 ng and 99.50％(n=9),respectively.Similarly,a linear relationship was observed for peiminine between the concentration and the peak area,spanning a range of 3.657 to 1.170 μg·mL-1,with a correlation coefficient of 0.999 1.The LOD and recovery rate for peiminine were 21.94 ng and 100.5％(n=9),respectively.In contrast,ELSD yielded LOD of 24.50 ng for peimine and 36.57 ng for peiminine,with linear range of double logarithmic fitting was 4.900 to 490.0 μg·mL-1 and 7.314 to 585.1 μg·mL-1,respectively.Conclusion:NQAD outperforms ELSD in the quantification of peimine and peiminine,offering superior accuracy,precision,and sensitivity,along with an extended dynamic linear range.By enabling direct content calculation via linear regression,it streamlines the process,bypassing the complex double logarithmic calculations.This approach not only boosts the efficiency of data handling but also substantially simplifies the computational steps,addressing the detection and analysis needs for peimine and peiminine in huangshi xiangsheng pills.

Objective:The study aimed to quantify the contents of peimine and peiminine in huangshi xiangsheng pills using a nano quantity analyte detector(NQAD)and compare the results with the evaporative light scattering detector(ELSD).Methods:Analytical separation was conducted utilizing a CAPCELL PAK MG Ⅲ C18 column(4.6 mm ×250 mm,5 μmi)as the stationary phase.The mobile phase consisted of a mixture of acetonitrile-water-diethylamine(65∶35∶0.03),with a flow rate set at 1.0 mL·min-1 and the column maintained at a temperature of 25℃.Results:NQAD analysis revealed a robust linear correlation between the concentration and the peak area for peimine within a concentration range of 2.450 to 1.470 μg·mL-1,achieving a correlation coefficient of 0.999 3.The limit of detection(LOD)and recovery rate for peimine were determined to be 14.70 ng and 99.50％(n=9),respectively.Similarly,a linear relationship was observed for peiminine between the concentration and the peak area,spanning a range of 3.657 to 1.170 μg·mL-1,with a correlation coefficient of 0.999 1.The LOD and recovery rate for peiminine were 21.94 ng and 100.5％(n=9),respectively.In contrast,ELSD yielded LOD of 24.50 ng for peimine and 36.57 ng for peiminine,with linear range of double logarithmic fitting was 4.900 to 490.0 μg·mL-1 and 7.314 to 585.1 μg·mL-1,respectively.Conclusion:NQAD outperforms ELSD in the quantification of peimine and peiminine,offering superior accuracy,precision,and sensitivity,along with an extended dynamic linear range.By enabling direct content calculation via linear regression,it streamlines the process,bypassing the complex double logarithmic calculations.This approach not only boosts the efficiency of data handling but also substantially simplifies the computational steps,addressing the detection and analysis needs for peimine and peiminine in huangshi xiangsheng pills.

ObjectiveTo investigate the effects of curcumin on type 2 diabetic neuropathic pain (DNP)and expression of inositol-requiring enzyme 1α (IRE1α) in spinal dorsal horn and dorsal root ganglia (DRG) in rats.MethodsType 2 diabetes mellitus was induced by high-fat and high-sucrose diet and intraperitoneal streptozotocin (STZ) 35 mg/kg,and confirmed by fasting blood glucose level ＞ 16.7 mmol/L in male SD rats.Type 2 DNP was confirmed by the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWI.) measured on day 14 after STZ administration ＜ 80％ of the baseline value.The rats were then randomly divided into 3 groups ( n =27 each):DNP group,curcumin group (group Cur) and solvent control group (group SC).Curcumin and corn oil 100 mg/kg (25 mg/ml) were given intraperitoneally once a day for 14 consecutive days starting from 14 days after administration of streptozocin in Cur and SC groups respectively.Another 27 rats were chosen and served as control group (group C) and fed with common fodders.MWT and TWL were measured at 3,7 and 14 day after curcumin administration.The expression of IRE1α in spinal dorsal horn and DRG was detected by Western blot.ResultsCompared with group C,MWT was significantly decreased and TWL was significantly shortened,and the expression of IRE1α was up-regulated in DNP,Cur,and SC groups (P ＜ 0,05),Compared with group DNP,MWT were significantly increased,TWL was significantly prolonged,and the expression of IRE1α in spinal dorsal horn and DRG was down-regulated in group Cur (P ＜ 0.05).There was no significantdifference in the parameters mentioned above between DNP and SC groups (P ＞ 0.05).ConclusionCurcumin can attenuate type 2 1)NP and inhibition of the expression of IRE1α in spinal dorsal horn and DRG is involved in the mechanism.