Edge Computing-Based Cloud Platform for Snakebite Assisted Diagnosis.

Snakebite is a major global public health problem, with more than 5 million snakebite victims recorded each year. Timely diagnosis and appropriate treatment of snakebite are the keys to preventing serious complications and improving the patient’s prognosis. However, most medical institutions lack experience in snakebite treatment, which is prone to misdiagnosis or even missed diagnosis, and serious cases endanger the lives of patients. Artificial intelligence is widely used in computer-aided diagnosis systems (CAD) and plays a vital role in snakebite recognition. In recent years, research has tended to build models, ignoring data preparation and analysis. Therefore, there is an urgent need for a rapid and accurate diagnostic method for snakebite to assist clinical diagnostic decision-making. We propose a snakebite auxiliary diagnosis system combining edge computing and machine learning technology. The system has the advantages of simple deployment, strong flexibility, and simple operation and is not limited by the equipment conditions of some grassroots hospitals. Experimental results show that this system can quickly and accurately diagnose the types of venomous snakes, overcome the limitations of traditional snakebite diagnosis methods in various aspects, and provide reliable real-time service tools for medical professionals, especially those in remote areas, allowing rapid diagnosis and treatment of snakebite cases, ultimately reducing morbidity and mortality.