4 Ways That AI will Affect Medical Computer Systems

The term “artificial intelligence” conjures images straight out of science fiction blockbusters: super-smart machines controlling all aspects of life, and often running wild to destroy their human creators. In reality, however, AI is very different… and in many ways, it’s already here.

Artificial intelligence is defined most prominently by an ability to perform human-like tasks. For instance, many AI programs are designed to learn over time, allowing them to analyze data more accurately and provide more sophisticated computing functions.

This impact can be felt most profoundly in the medical industry, which is already undergoing a technological revolution thanks to modern medical computer systems. The advent of AI will affect such systems considerably, and in a few years may become an integral part of any medical organization. Those hoping to take advantage of the enormous potential of AI applications would do well to start preparing for it now.

So what does that mean? It means taking a close look at the ways that AI will affect medical-grade PCs and ensuring that the units in your network are prepared for it. Here are 4 specific things to look for.

Upgradable Components Add Processing Power

AI relies on typical hardware concerns, which come down to processing power and storage space. The faster a computer can perform and the more space it has to hold information, the better it can do its job. Consider, for example, the vital task of data analysis. An AI program can analyze a huge amount of medical records very quickly in order to spot trends in treatment plans and places where errors seem to recur. (This is already happening in places like the Cleveland Clinic, where IBM’s Watson program is used to conduct deep data mining of existing medical records.)

In order to do that, it needs a system with a great deal of memory and processing power, and implementing such a program may require you to replace older computers that lack the capacity. Alternately, looking at an upgradable system now – with the ability to upgrade ram, add a second hard drive or even upgrade the CPU with more powerful versions in the future – will allow your network to adjust to increased needs and better take on the requirements of an artificial intelligence system.

Superior Imaging Helps AI Do Its Job

Diagnostic imaging PCs and similar devices help enhance the images doctors need to perform diagnoses: anything from x-rays of broken bones to endoscopes pinpointing problems in the patient’s gastrointestinal tract. But imaging analysis can take a long time, as medical personnel pore over numerous images in search of accurate information. That means a significant loss of efficiency at best, and if the needed information is time-specific – if, for example, the information is required before emergency surgery – it can be dangerous.

3D medical scans benefit immeasurably from AI features, which can analyze visual data much faster and with greater accuracy than humans. (MIT has developed an algorithm called VoxelMorph for just such analyses.) But that, in turn, relies on high-quality imaging from the computer itself, which provides better data samples and can improve accuracy. A system with a high-end video card and superior image processing will be well-suited to AI image diagnostics, and allow such applications to perform their functions effectively.

Everything Is Connected

Accurate analysis depends on accurate data, and that can rely on devices that aren’t necessarily set up for an AI application. An older x-ray machine, for instance, may use outdated image files that are not readily integrated into a newer medical computer network. Patient data, medication supplies and similar details may also suffer from interconnection issues (such as when they are recorded by hand and logged into an electronic system later).

The more interconnectivity a network has, the more readily such data can be analyzed and interpreted by an AI system. That starts with peripheral equipment, such as 2D barcode scanners and RFID devices. When directly integrated into a medical tablet or computer on wheels, they allow nurses and doctors to instantly scan patient data by swiping the scanner over medical bracelets, as well as scanning barcodes on medication bottles and even medical equipment.

Similarly, legacy ports such as RS-232 ports on a medical computer provide access for older machines. That, in turn, allows an AI application to analyze the data from a legacy device with considerable speed and efficiency. The more you can address interconnectivity with a system designed for AI functions, the more smoothly it will run with other equipment, and the more quality data will be procured for its use.

 

Cybernet Manufacturing produces a variety of medical grade PCs to facilitate artificial intelligence applications. If your organization is looking at the potential of AI for your network, contact our team to discuss your options.