Fetal macrosomia is associated with maternal and newborn complications due to incorrect fetal weight estimation or inappropriate choice of delivery models.The early screening and evaluation of macrosomia in the third ...Fetal macrosomia is associated with maternal and newborn complications due to incorrect fetal weight estimation or inappropriate choice of delivery models.The early screening and evaluation of macrosomia in the third trimester can improve delivery outcomes and reduce complications.However,traditional clinical and ultrasound examinations face difficulties in obtaining accurate fetal measurements during the third trimester of pregnancy.This study aims to develop a comprehensive predictive model for detecting macrosomia using machine learning(ML)algorithms.The accuracy of macrosomia prediction using logistic regression,k-nearest neighbors,support vector machine,random forest(RF),XGBoost,and LightGBM algorithms was explored.Each approach was trained and validated using data from 3244 pregnant women at a hospital in southern China.The information gain method was employed to identify deterministic features associated with the occurrence of macrosomia.The performance of six ML algorithms based on the recall and area under the curve evaluation metrics were compared.To develop an efficient prediction model,two sets of experiments based on ultrasound examination records within 1-7 days and 8-14 days prior to delivery were conducted.The ensemble model,comprising the RF,XGBoost,and LightGBM algorithms,showed encouraging results.For each experimental group,the proposed ensemble model outperformed other ML approaches and the tra-ditional Hadlock formula.The experimental results indicate that,with the most risk-relevant features,the ML algo-rithms presented in this study can predict macrosomia and assist obstetricians in selecting more appropriate delivery models.展开更多
Insect repellent DEET and sunscreen ingredient oxybenzone play an essential role in minimizing vector-borne diseases and skin cancers.The purpose of this study was to investigate the effects of emulsion type,addition ...Insect repellent DEET and sunscreen ingredient oxybenzone play an essential role in minimizing vector-borne diseases and skin cancers.The purpose of this study was to investigate the effects of emulsion type,addition of thickening agent and droplet size in three emulsion-based lotions on percutaneous permeation of DEET and oxybenzone using in vitro diffusion experiments,in order to minimize overall systemic permeation of the substances.Formulation C(water-in-oil emulsion)significantly increased overall permeation of DEET through human skin(56%)compared to Formulation A(oil-in-water emulsion).Formulation B(oil-in-water emulsion with thickening agent xanthan gum)significantly decreased the size of oil droplet containing DEET(16%),but no effect on oil droplets containing oxybenzone.Adding xanthan gum also increased overall permeation of DEET and oxybenzone(21%and 150%)when compared to Formulation A;presence of both ingredients in Formulation B further increased their permeation(36%and 23%)in comparison to its single counterparts.Overall permeation of oxybenzone through LDPE was significantly higher by 26%-628%than that through human skin;overall permeation of DEET through human skin was significantly higher by 64%-338%than that through LDPE.展开更多
基金supported by the High Level-Hospital Program,Health Commission of Guangdong Province,China,No.HKUSZH201901011the Shenzhen Science and Technology Program,No.JCYJ20220530142017038.
文摘Fetal macrosomia is associated with maternal and newborn complications due to incorrect fetal weight estimation or inappropriate choice of delivery models.The early screening and evaluation of macrosomia in the third trimester can improve delivery outcomes and reduce complications.However,traditional clinical and ultrasound examinations face difficulties in obtaining accurate fetal measurements during the third trimester of pregnancy.This study aims to develop a comprehensive predictive model for detecting macrosomia using machine learning(ML)algorithms.The accuracy of macrosomia prediction using logistic regression,k-nearest neighbors,support vector machine,random forest(RF),XGBoost,and LightGBM algorithms was explored.Each approach was trained and validated using data from 3244 pregnant women at a hospital in southern China.The information gain method was employed to identify deterministic features associated with the occurrence of macrosomia.The performance of six ML algorithms based on the recall and area under the curve evaluation metrics were compared.To develop an efficient prediction model,two sets of experiments based on ultrasound examination records within 1-7 days and 8-14 days prior to delivery were conducted.The ensemble model,comprising the RF,XGBoost,and LightGBM algorithms,showed encouraging results.For each experimental group,the proposed ensemble model outperformed other ML approaches and the tra-ditional Hadlock formula.The experimental results indicate that,with the most risk-relevant features,the ML algo-rithms presented in this study can predict macrosomia and assist obstetricians in selecting more appropriate delivery models.
基金support from Canada Foundation for Innovation(CFI)Manitoba Institute of Child Health(MICH)graduate studentship from MHRC(TW).
文摘Insect repellent DEET and sunscreen ingredient oxybenzone play an essential role in minimizing vector-borne diseases and skin cancers.The purpose of this study was to investigate the effects of emulsion type,addition of thickening agent and droplet size in three emulsion-based lotions on percutaneous permeation of DEET and oxybenzone using in vitro diffusion experiments,in order to minimize overall systemic permeation of the substances.Formulation C(water-in-oil emulsion)significantly increased overall permeation of DEET through human skin(56%)compared to Formulation A(oil-in-water emulsion).Formulation B(oil-in-water emulsion with thickening agent xanthan gum)significantly decreased the size of oil droplet containing DEET(16%),but no effect on oil droplets containing oxybenzone.Adding xanthan gum also increased overall permeation of DEET and oxybenzone(21%and 150%)when compared to Formulation A;presence of both ingredients in Formulation B further increased their permeation(36%and 23%)in comparison to its single counterparts.Overall permeation of oxybenzone through LDPE was significantly higher by 26%-628%than that through human skin;overall permeation of DEET through human skin was significantly higher by 64%-338%than that through LDPE.
