Design of Portable Spirometer Based on Internet of Things of Medicine / 中国医疗器械杂志

A kind of portable device for detecting common lung function parameters is mentioned in this paper. Using the singlechip microcomputer as the master control block to collect and process the data from high-accuracy gas pressure sensor, through the way of parametric calibration and linear interpolation to test and calculate the Forced Vital Capacity (FVC), Peak Expiratory Flow (PEF), Forced Expiratory Volume in one second (FEV1), and FEV1/FVC. Meanwhile, the detected parameters can be uploaded to the intelligent mobile terminal through the wireless transmission module. The device is able to show expiratory volume-time curve and the final parameters clearly, the error of measurement is less than 5%. In addition, that device is small and convenient, not only is good for clinical application, but also can be used for family in a house.

Drug-target protein interaction prediction based on AdaBoost algorithm / 生物医学工程学杂志

The drug-target protein interaction prediction can be used for the discovery of new drug effects. Recent studies often focus on the prediction of an independent matrix filling algorithm, which apply a single algorithm to predict the drug-target protein interaction. The single-model matrix-filling algorithms have low accuracy, so it is difficult to obtain satisfactory results in the prediction of drug-target protein interaction. AdaBoost algorithm is a strong multiple classifier combination framework, which is proved by the past researches in classification applications. The drug-target interaction prediction is a matrix filling problem. Therefore, we need to adjust the matrix filling problem to a classification problem before predicting the interaction among drug-target protein. We make full use of the AdaBoost algorithm framework to integrate several weak classifiers to improve performance and make accurate prediction of drug-target protein interaction. Experimental results based on the metric datasets show that our algorithm outperforms the other state-of-the-art approaches and classical methods in accuracy. Our algorithm can overcome the limitations of the single algorithm based on machine learning method, exploit the hidden factors better and improve the accuracy of prediction effectively.

Analysis of the Utilization of Lipid-regulating Agents from 74 Hospitals in 6 Areas of China in 2013 / 中国药房

OBJECTIVE:To provide reference for drug procurement and supply and rational use of lipid-regulating agents. METHODS:The epidemiological investigation was carried out among 159 506 cases from 74 hospitals in Beijing,Chengdu, Guangzhou,Hangzhou,Shanghai and Tianjin in 2013. The utilization of lipid-regulating agents was analyzed statistically in re-spects of purchase value,DDDs,DDC,actual average daily dose and sort ratio. RESULTS:The prevalence rate of hyperlipidemia was relatively high,accounting for 29.56% and showing a tendency of regional distribution and young age in all regions. The pa-tients with hypertension,diabetes and coronary heart disease had a higher incidence to suffer from hyperlipidemia. The use of atorv-astatin was in the first place,but it also had a higher DDC;while rosuvastatin hasd the advantage over aorvastatin in drug market. Simvastatin had a lower DDC and was more suitable for the patients with low income. The doses of lipid-regulating agents in other regions were lower than DDD except for those in Beijing and Tianjin. CONCLUSIONS:Statins dominate the lipid-regulating agents market. But new lipid-regulating agents and drug combination provide a new choice for clinical treatment.