Tuberculosis (TB) is one of the major public health concerns worldwide. Since the development of precision medicine, the filed regarding TB control and prevention has been brought into the era of precision medicine. Although great progress has been achieved in the accurate diagnosis, treatment and management of TB patients, we have to face several challenges. We should seize the opportunity, and develop and improve novel measures in TB prevention on the basis of precision medicine. The accurate diagnosis criteria, treatment regimen and management of TB patients should be carried out according to the standard of precision medicine. We aim to improve the treatment of TB patients and prevent the transmission of TB in the community, thereby contributing to the achievement of the End TB Strategy by 2035.
Electrocardiogram (ECG) signal is an important basis for the diagnosis of arrhythmia and myocardial infarction. In order to further improve the classification effect of arrhythmia and myocardial infarction, an ECG classification algorithm based on Convolutional vision Transformer (CvT) and multimodal image fusion was proposed. Through Gramian summation angular field (GASF), Gramian difference angular field (GADF) and recurrence plot (RP), the one-dimensional ECG signal was converted into three different modes of two-dimensional images, and fused into a multimodal fusion image containing more features. The CvT-13 model could take into account local and global information when processing the fused image, thus effectively improving the classification performance. On the MIT-BIH arrhythmia dataset and the PTB myocardial infarction dataset, the algorithm achieved a combined accuracy of 99.9% for the classification of five arrhythmias and 99.8% for the classification of myocardial infarction. The experiments show that the high-precision computer-assisted intelligent classification method is superior and can effectively improve the diagnostic efficiency of arrhythmia as well as myocardial infarction and other cardiac diseases.
Objective To investigate the current prevalence of cerebral stroke and hypertension in Ganzi Tibetan state, so as to control stroke and hypertension in future. Methods A representative people sample of Kangding, Dege, Ganzi, Litang and Batang county was selected through randomized cluster sampling. Data of demographic characteristics, hypertension and stroke status were collected by face-to-face interview. Results 5 049 people were included, of which 48.6% were male, and 51.4% were female. The prevalence rate of hypertension and stroke were 23.4% and 1 894/100 000 respectively. The population with hypertension had high prevalence of stroke. The prevalence increased along with the age. Conclusions The prevalence of hypertension and stroke is high in Ganzi Tibetan state. The causes may be ascribed to special geography surroundings and life style. It is very important to pay more attention to prevent and control of hypertension and stroke in this area.