Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

Objective:To analyze the changes in the costs of hospital rehabilitation after the reform of health insurance payments in the past 6 years, and to identify relevant factors which can provide a reference for the reform of the health insurance payment system in rehabilitation department.Methods:Information on 16, 827 patients hospitalized in the rehabilitation department of The First Affiliated Hospital of Xi′an Jiaotong University between May 2018 and May 2024 was collected and subjected to non-parametric analysis.Results:The average hospitalization cost of rehabilitation department patients over the six years was Y14, 574.92±10, 524.79. During that time the proportion of the cost attributable to Western medicine decreased from 17.1% in 2018 to 7.6% in 2024. The proportion of the patients with hypertension was 51.94%, followed by diabetes mellitus (20.10%). Those with infections had the highest total hospitalization costs. Motor disorders were the most common dysfunction (59.02%), followed by speech disorders (17.45%). Patients with swallowing disorders had the highest hospitalization costs. After the payment system shifted from fee-for-service (FFS) to payment by diagnosis-related group (DRG) in 2023, the average daily inpatient expenditures for rehabilitation patients with all types of diseases gradually declined, reaching its lowest level in 2024.Conclusions:After the health insurance payments shifted from FFS to DRG, the proportion of in patients′ total drug costs decreased annually, and the average daily costs of patients with different types of diseases also decreased significantly, but the comprehensive service fee and diagnostic costs increased.

As a major category of occupational hazards in China, physical factors are widely distributed in various industries and affect a large number of workers. The list and diagnostic criteria of occupational diseases caused by physical factors are important basis for occupational disease diagnosis and protection of occupational health rights and interests for occupational populations. This article compares the differences in the list of occupational diseases caused by physical factors at home and abroad, analyzes the problems in the current list of occupational diseases caused by physical factors and related diagnostic standards in China, and puts forward relevant suggestions for further adjusting the list of occupational diseases caused by physical factors, formulating and revising relevant diagnostic standards for occupational diseases, providing reference for improving the classification and catalogue of occupational diseases in China in the future.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

As a major category of occupational hazards in China, physical factors are widely distributed in various industries and affect a large number of workers. The list and diagnostic criteria of occupational diseases caused by physical factors are important basis for occupational disease diagnosis and protection of occupational health rights and interests for occupational populations. This article compares the differences in the list of occupational diseases caused by physical factors at home and abroad, analyzes the problems in the current list of occupational diseases caused by physical factors and related diagnostic standards in China, and puts forward relevant suggestions for further adjusting the list of occupational diseases caused by physical factors, formulating and revising relevant diagnostic standards for occupational diseases, providing reference for improving the classification and catalogue of occupational diseases in China in the future.