There are many benefits that edge AI brings to Healthcare. In fact, its characteristics have a positive effect on the management and processing of data generated every day by hospitals, clinics and telemedicine devices directly at the sources or in their vicinity. This eliminates the need for a central repository and bandwidth and latency no longer constitute obstacles to the use of this data.
Speeding up the use of digital tools means that, for example, in diagnostic imaging, thanks to AI, ultrasonic readings and radiographs can be processed directly on the device in use, reducing privacy problems and providing real-time support to doctors performing tests. A similar argument can be made for patient monitoring and therapeutic treatment: Edge AI provides new opportunities for healthcare that is increasingly in line with the needs of citizens.
Edge AI in healthcare: more efficient data management
Edge computing presupposes a physical infrastructure that, by being located outside of a cloud configuration or data center, allows the staff of a healthcare organization to acquire and analyze clinical information and patient data locally and quickly.
This, combined with the processing capacity that allows Artificial Intelligence to be available when applied to medical devices, provides great support to doctors who can receive effective indications during the analysis of patients to reach accurate diagnoses more quickly. Any device with an internet connection can have its own processor and storage unit, allowing more efficient information management wherever you are.
Edge computing, a network of small autonomous data centers for healthcare
Edge computing makes it possible to reduce the inefficiency associated with moving all data to a centralized point, creating a sort of network of small data centers with dedicated purposes and functions, to meet the specific needs of healthcare. Activities that create or require data processing can be carried out much faster when the computing power is close to the device that generates them. However, by functioning differently than a traditional data center, edge computing is a significant change for healthcare in the way information is processed, managed and provided to end users.
4 edge computing healthcare applications
Let’s see 4 practical applications to better understand the advantages of edge computing in healthcare,
1. Faster and more accurate diagnosis
Within hospitals, edge computing and Artificial Intelligence allow for more accurate and faster diagnoses. Therefore, on the one hand, they provide an important support to doctors in identifying details that could have escaped them. On the other hand they provide a benefit to patients who receive a more precise diagnosis in a shorter space of time. Thanks to the possibility of using wearable devices, it is possible to continuously monitor patients and intervene in a timely and proactive manner should, thanks to AI, the analysis of the variation of certain parameters predict the occurrence of difficult situations.
2. The evolution of ambulances
In the present day, ambulances are mainly used to transport patients to hospitals as quickly as possible. However, they are gradually evolving into first aid stations, through a full supply of IoT interconnected devices that can help save people’s lives. There are several practical examples of this. Some ambulances allow you to share the vital parameters of the transported patient in real time, allowing you to make high-resolution video calls to your doctor remotely. This allows you to take advantage of the time that elapses upon arrival at the hospital to make diagnoses and also to intervene on certain pathologies. But there’s more. Some ambulances are implementing edge computing on board to use augmented reality as a tool to improve emergency management through the vision of complex rescue protocols.
3. Data collection in operating rooms
During surgery, it is necessary to record every action, from the patient entering the room to the final cleaning, which can be a particularly time-consuming procedure. Using cameras and edge computing devices, Artificial Intelligence software can automatically record and categorize every action within an operating room, checking that all the equipment and materials necessary for an operation are present. Operators can therefore focus exclusively on the patient.
The use of on-the-edge sensors makes it possible to provide telemedicine services and monitor patients in their homes, gathering information useful to outline clinical situations, and possibly alert caregivers of changes in health conditions that require changes to treatments.
Safer data with edge computing in Healthcare
It is easy to understand that data security is vital in healthcare. IDC, the International Data Corporation, the world’s largest research company, says 31% of healthcare organizations are using edge solutions not so much for health-related processing but as assets to ensure data security and protection.
Local information storage is not only cheaper but it also helps protect the privacy of sensitive and highly regulated data. Underlying this is the fact that an edge data center handles less data than a central data center, reducing the risk of adverse technical events or cybercrime compromising important resources. Any threats can then be monitored close to the source almost in real time, promoting a proactive approach to security.