Clinical Analysis of Medical IoT and Acute Cerebral Infarction Based on Image Recognition

Abstract

Due to the mutual penetration and development of clinical medicine and informatics, medical image recognition can avoid the influence of subjective factors, and can diagnose the types of benign and malignant tumors in a timely and accurate manner, which is especially important for formulating effective treatment plans. This work mainly discusses fuzzy clustering and segmentation and SVM detection algorithms application in clinical medicine. The Internet of Things technology is a high-tech from the branch of the Internet, which plays a huge role in promoting the development and innovation of modern healthcare companies. The application of the Internet of Things technology has greatly changed the traditional medical model and effectively improved the relatively independent model in each unit system, thereby effectively promoting the scientific and informatization of modern intelligent medical care. Acute cerebral infarction is one of the most common clinical diseases, the clinical manifestations usually include tinnitus, headache, nausea, and vomiting. Acute cerebral infarction usually occurs suddenly and develops rapidly, which may eventually lead to hemiplegia, sensory disturbance, and language disturbance. This article analyzes the role of image recognition based on the medical Internet of Things in the clinical analysis of acute cerebral infarction and illustrates the clinical treatment methods through case studies. Simulation results prove that advanced IoT technology can more accurately track and monitor relevant patient information and can also play an important role in patient monitoring.