Multitask Interactive Attention Learning Model Based on Hand Images for Assisting Chinese Medicine in Predicting Myocardial Infarction

Abstract

Acute myocardial infarction (AMI) is one of the most serious and dangerous cardiovascular diseases. In recent years, the number of patients around the world has been increasing significantly, among which people under the age of 45 have become the high-risk group for sudden death of AMI. AMI occurs quickly and does not show obvious symptoms before onset. In addition, postonset clinical testing is also a complex and invasive test, which may cause some postoperative complications. Therefore, it is necessary to propose a noninvasive and convenient auxiliary diagnostic method. In traditional Chinese medicine (TCM), it is an effective auxiliary diagnostic strategy to complete the disease diagnosis through some body surface features. It is helpful to observe whether the palmar thenar undergoes hypertrophy and whether the metacarpophalangeal joint is swelling in detecting acute myocardial infarction. Combined with deep learning, we propose a depth model based on traditional palm image (MTIALM), which can help doctors of traditional Chinese medicine to predict myocardial infarction. By building the shared network, the model learns information that covers all the tasks. In addition, task-specific attention branch networks are built to simultaneously detect the symptoms of different parts of the palm. The information interaction module (IIM) is proposed to further integrate the information between task branches to ensure that the model learns as many features as possible. Experimental results show that the accuracy of our model in the detection of metacarpophalangeal joints and palmar thenar is 83.16% and 84.15%, respectively, which are significantly improved compared with the traditional classification methods.

Interactive Music Learning Model Based on RBF Algorithm

“…erefore, teachers need to actively guide students through classroom instruction, use motivating and effective assessments (individual classroom extra credit, group assessment, and music grade percentages), and provide opportunities for students to demonstrate their musical skills in order to create a strong desire to learn creative writing. By constructing an "interactive" learning model, it is clear that students' thinking skills are enhanced and their individual musical perception, participation, confidence, and expression are strengthened [27][28][29][30][31][32][33][34][35]. In terms of knowledge, experience, personality, spirit, culture, etc., the vision is enhanced, life is empathized and experienced, life is enlightened, and spirituality is enriched, and the direction of development of teachers and students tends to the realm of truth and beauty.…”

High performance of privacy-preserving acute myocardial infarction auxiliary diagnosis based on federated learning: a multicenter retrospective study

“…Several diagnostic models have been developed based on artificial intelligence (15)(16)(17)(18). Du et al reported that a system model based on improved machine learning showed a certain effect in their clinical analysis of AMI (17).…”

“…Du et al reported that a system model based on improved machine learning showed a certain effect in their clinical analysis of AMI ( 17 ). Wang et al established a multitask interactive attention learning model and found it could improve the diagnostic efficiency of AMI ( 18 ). However, privacy security risks have hindered the development of artificial intelligence-based diagnostic models in AMI and other diseases.…”