Background:Pneumoconioses,a group of occupational lung diseases caused by inhalation of mineral dust,pose significant health risks to affected individuals.Accurate assessment of profusion(extent of lung involvement)in...Background:Pneumoconioses,a group of occupational lung diseases caused by inhalation of mineral dust,pose significant health risks to affected individuals.Accurate assessment of profusion(extent of lung involvement)in chest radiographs is essential for screening,diagnosis and monitoring of the diseases along with epidemiological classification.This study explores an automated classification system combining U-Net-based segmentation for lung field delineation and DenseNet121 with ImageNet-based transfer learning for profusion classification.Methods:Lung field segmentation using U-Net achieved precise delineation,ensuring accurate region-of-interest definition.Transfer learning with DenseNet121 leveraged pre-trained knowledge from ImageNet,minimizing the need for extensive training.The model was fine-tuned with International Labour Organization(ILO)-2022 version standard chest radiographs and evaluated on a diverse dataset of ILO-2000 version standardized radiographs.Results:The U-Net-based segmentation demonstrated robust performance(Accuracy 94%and Dice Coefficient 90%),facilitating subsequent profusion classification.The DenseNet121-based transfer learning model exhibited high accuracy(95%),precision(92%),and recall(94%)for classifying four profusion levels on test ILO 2000/2011D dataset.The final Evaluation on ILO-2000 radiographs highlighted its generalization capability.Conclusion:The proposed system offers clinical promise,aiding radiologists,pulmonologists,general physicians,and occupational health specialists in pneumoconioses screening,diagnosis,monitoring and epidemiological classification.Best of our knowledge,this is the first work in the field of automated Classification of Profusion in Chest Radiographs of Pneumoconioses based on recently published latest ILO-2022 standard.Future research should focus on further refinement and real-world validation.This approach exemplifies the potential of deep learning for enhancing the accuracy and efficiency of pneumoconioses assessment,benefiting industrial workers,patients,and healthcare providers.展开更多
Objective To observe the clinical efficacy of Jiāwèi Wǔbèizǐ sǎn（加味五倍子散,Supplemented Galla Chinensis Powder） application on the different syndromes of profuse sweating after tumor chemotherapy.Me...Objective To observe the clinical efficacy of Jiāwèi Wǔbèizǐ sǎn（加味五倍子散,Supplemented Galla Chinensis Powder） application on the different syndromes of profuse sweating after tumor chemotherapy.Methods One hundred and sixty patients with profuse sweating after tumor chemotherapy were randomly divided into a control group（n=80） and a treatment group（n=80）.Placebo application was carried out in the control group,and traditional Chinese medicine application was conducted in the treatment group.Treatment for 7 days was considered as 1 course of treatment.Results In treatment group,48 patients were cured,improvement was found in25 cases,and ineffectiveness was seen in 7 cases.For the patients with lungwei insecurity syndrome,19 cases were cured,improvement was found in10 cases,and ineffectiveness was seen in 1 case;for the patients with deficiency of both qi and yin,27 cases were cured,improvement was found in 9 cases,and ineffectiveness was seen in 2 cases;for the patients with vigorous fire due to yin deficiency,3 cases were cured,improvement was found in5 cases,and ineffectiveness was seen in 4 cases.According to statistical analysis,the total efficacy of treatment group was superior to that of control group（P0.05）.The efficacy on lung-wei insecurity and deficiency of both qi and yin of treatment group was superior to that of control group（both P0.05）,but there was no obvious difference between treatment group and control group in the efficacy on vigorous fire due to yin deficiency（P0.05）.Conclusion Supplemented Galla Chinensis Powder application on the navel can effectively improve the profuse sweating syndrome of patients in the types of lung-wei insecurity and deficiency of both qi and yin after tumor chemotherapy,but the efficacy is not so good for the patients in the type of vigorous fire due to yin deficiency.展开更多
文摘Background:Pneumoconioses,a group of occupational lung diseases caused by inhalation of mineral dust,pose significant health risks to affected individuals.Accurate assessment of profusion(extent of lung involvement)in chest radiographs is essential for screening,diagnosis and monitoring of the diseases along with epidemiological classification.This study explores an automated classification system combining U-Net-based segmentation for lung field delineation and DenseNet121 with ImageNet-based transfer learning for profusion classification.Methods:Lung field segmentation using U-Net achieved precise delineation,ensuring accurate region-of-interest definition.Transfer learning with DenseNet121 leveraged pre-trained knowledge from ImageNet,minimizing the need for extensive training.The model was fine-tuned with International Labour Organization(ILO)-2022 version standard chest radiographs and evaluated on a diverse dataset of ILO-2000 version standardized radiographs.Results:The U-Net-based segmentation demonstrated robust performance(Accuracy 94%and Dice Coefficient 90%),facilitating subsequent profusion classification.The DenseNet121-based transfer learning model exhibited high accuracy(95%),precision(92%),and recall(94%)for classifying four profusion levels on test ILO 2000/2011D dataset.The final Evaluation on ILO-2000 radiographs highlighted its generalization capability.Conclusion:The proposed system offers clinical promise,aiding radiologists,pulmonologists,general physicians,and occupational health specialists in pneumoconioses screening,diagnosis,monitoring and epidemiological classification.Best of our knowledge,this is the first work in the field of automated Classification of Profusion in Chest Radiographs of Pneumoconioses based on recently published latest ILO-2022 standard.Future research should focus on further refinement and real-world validation.This approach exemplifies the potential of deep learning for enhancing the accuracy and efficiency of pneumoconioses assessment,benefiting industrial workers,patients,and healthcare providers.
基金Supported by Scientific research fund project of Yancheng,Jiangsu:YK2014111
文摘Objective To observe the clinical efficacy of Jiāwèi Wǔbèizǐ sǎn（加味五倍子散,Supplemented Galla Chinensis Powder） application on the different syndromes of profuse sweating after tumor chemotherapy.Methods One hundred and sixty patients with profuse sweating after tumor chemotherapy were randomly divided into a control group（n=80） and a treatment group（n=80）.Placebo application was carried out in the control group,and traditional Chinese medicine application was conducted in the treatment group.Treatment for 7 days was considered as 1 course of treatment.Results In treatment group,48 patients were cured,improvement was found in25 cases,and ineffectiveness was seen in 7 cases.For the patients with lungwei insecurity syndrome,19 cases were cured,improvement was found in10 cases,and ineffectiveness was seen in 1 case;for the patients with deficiency of both qi and yin,27 cases were cured,improvement was found in 9 cases,and ineffectiveness was seen in 2 cases;for the patients with vigorous fire due to yin deficiency,3 cases were cured,improvement was found in5 cases,and ineffectiveness was seen in 4 cases.According to statistical analysis,the total efficacy of treatment group was superior to that of control group（P0.05）.The efficacy on lung-wei insecurity and deficiency of both qi and yin of treatment group was superior to that of control group（both P0.05）,but there was no obvious difference between treatment group and control group in the efficacy on vigorous fire due to yin deficiency（P0.05）.Conclusion Supplemented Galla Chinensis Powder application on the navel can effectively improve the profuse sweating syndrome of patients in the types of lung-wei insecurity and deficiency of both qi and yin after tumor chemotherapy,but the efficacy is not so good for the patients in the type of vigorous fire due to yin deficiency.
