Chronic Obstructive Pulmonary Disease (copd) is a life-threatening lung ailment and a significant cause of morbidity and fatality globally. The early detection of copd can provide timely proper medication and reduce t...
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Chronic Obstructive Pulmonary Disease (copd) is a life-threatening lung ailment and a significant cause of morbidity and fatality globally. The early detection of copd can provide timely proper medication and reduce the mortality rate. To obtain proper treatment and lessen the death rate, this study proposes a novel ensemble model: the Multistage Ensemble model (MSEN) with an optimized weighted voting technique to detect copd early and help clinicians provide proper and timely medication. In this study, there are two pools of classifiers created in which four classifiers are placed in each pool. These two pools of classifiers are employed to form two weighted ensemble models based on a weighted voting strategy. This study combines those generated ensemble models using a weighted voting technique to form an MSEN model. The genetic algorithm is utilized to optimize the hyperparameters of each classifier in each pool. The weights of two generated ensemble models and each classifier are optimized using the grid search technique. This study employs the K-Nearest Neighbors approach to fill in the missing values, isolation forest to remove the outliers, and the LightGBM with Recursive Feature Elimination for feature selection. An evaluation of the suggested MSEN model is conducted on a real-world Exasens dataset to validate the suggested model's effectiveness which exhibits that the proposed model obtains better performance to detect copd and provides superior performance than other machine learning models and existing benchmark techniques.
Study objectives: To investigate the technical properties and user friendliness of 10 office spirometers devoted for use in general practice, and to compare the results with standard diagnostic spirometers. Design: Mu...
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Study objectives: To investigate the technical properties and user friendliness of 10 office spirometers devoted for use in general practice, and to compare the results with standard diagnostic spirometers. Design: Multicenter study. Setting: Ten spirometer models were tested independently in three pulmonary function laboratories and by three general practitioners (GPs). Measurements: The laboratories studied the technical quality of the office spirometers in terms of precision and agreement with standard spirometers, whereas the three GPs assessed their user friendliness. The spirometers tested were as follows: Spirobank (Medical International Research;Rome, Italy);Simplicity (Puritan Bennett;Pleasanton, CA);OneFlow (Clement Clarke International;Harlow, Essex, UK);Datospir 70 (Sibelmed;Barcelona, Spain);Datospir 120 (Sibelmed);SpiroPro (SensorMedics;Yorba Linda, CA);EasyOne (NDD;Zurich, Switzerland);MicroLoop (Micro Medical;Chatham, Kent, UK);SpiroStar (Medikro;Kuopio, Finland);and Pneumotrae (Vitalograph;Maids Moreton, Buckingham, UK). FVC and FEV1 were measured in 399 subjects. User friendliness was assessed by the three GPs using a questionnaire. Results: The precision of FEV1 of the office and standard spirometers was comparable, but three office spirometers had > 200 mL limits of precision for FVC. Some devices presented a proportional difference on the FEV, with standard spirometers, underestimating the small values. The limits of agreements between standard and some office spirometers for FEV1/FVC ratio was > 10%. The overall user friendliness was estimated as good. Conclusions: The global quality and user friendliness of several office spirometers make them acceptable for the detection of copd, although differences between the laboratory and some of the office spirometers values suggest that the misclassification rates may be increased when using some models of office spirometers.
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