Tag Archives: artificial intelligence

AI Healthcare

Is Your Hospital Ready for the Future of AI?

Leaps in computing power, programming abilities, and the web of interconnected devices has created a boom in artificial intelligence.

A.I. will undoubtedly improve, disrupt, and alter every industry in the world, but it’s in healthcare that it could make the strongest impact. Artificial intelligence could one day be the ultimate medicine — if knowledge is power, then infinite, bespoke knowledge on any medical condition or patient could provide clinicians with their greatest tools yet.

With medical tablets and medical computers providing the necessary digital infrastructure, the following advances in AI might be deployable very soon in healthcare facilities around the globe.

The American AI Initiative Moves Forward

On February 12th, the “American AI Initiative” executive order was signed, with the intent to foster and improve the development of artificial intelligence in the United States. It serves to outline the country’s AI policy going forward, showing a commitment to further development of the technology and law that could have an enormous impact on healthcare technology.

Obviously, the idea is to spur innovation and funding in all areas of AI, but considering how poised the healthcare industry already is to take advantage of this area of technology, the signing of this order could have an enormous impact on hospitals in the near future.

The executive order is separated into five pillars: funding, government resources, international engagement, standardization, and automation.

The funding aid is obvious — innovation doesn’t happen without dedicated cash flows. The “government resources” pillar allows researchers to make use of federal data to help their experiments, while the “international engagement” pillar pushes for cooperation between the US and other nations who are also heavily involved in the development of AI. The “standardization” pillar is of particular use to healthcare and medical computers, because it doubles down on ensuring that ALL companies and developers will be able to interconnect their systems to everyone’s benefit.

With the assortment of EHR systems, medical computer systems, and even hospital-specific programs that are in use, a “one standard to rule them all” could prevent another Apple vs. PC format war that would only end up hurting hospitals and consumers.

Aiding the Visually Impaired

The data gathered and processed by AI is already being used to help blind and visually impaired people.

It began with apps like NavCog, which used Bluetooth beacons scattered around an indoor space to allow a blind person to navigate with the help of their phone. While it can (and is used) for homes, the system has also been deployed in places like hotels and hospitals to assist the visually impaired.

The next generation of the technology, however, involves the use of a suitcase-like device that leverages artificial intelligence and laser-navigation lidar to create a real-time picture of the immediate environment. This “suitcase AI” could then relay that information, and help guide the user through audio cues.

Amazon, Google, and many other tech giants are already jumping into this same field, developing apps, programs, and hardware that could be of great use to not only the impaired, but to healthcare or elderly facilities as well.

AI Chatbots Helping Patients and Doctors

The importance of patient engagement and telehealth are well known at this point, but perhaps what isn’t as widespread is the idea that medical computers, and specifically A.I., just may be the key to pulling it off. All of healthcare is understaffed, which is why a little help from computers could be just what the doctor ordered.

Chatbots like Babylon Health almost function as full-fledged telehealth options in their own right. The AI chatbot uses a database of medical information and, when compared against the patient’s medical history and symptoms, can help a patient do the preliminary research on any medical complaints before they see a doctor. With text or voice chat support, patients can simply tell the chatbot their symptoms and get a relatively accurate solution. It won’t replace the hospital, but it’s a wonderful starting place for any patient — and saves the Urgent Care lobby from looking like Woodstock.

For older, forgetful, or simply busy patients, consider pointing them toward “Florence,” a personal AI nurse. Florence can remind patients to take their medicine (at whatever interval is desired), and can help track weight loss, menstrual cycles, and even mood and mental health.

A chatbot like “Safedrugbot” is actually for clinicians, a quick app/chat message service that allows doctors to ask about what drugs are safe to use for breastfeeding mothers. It even includes information about alternate medications.

These interactive AI are only the first step in augmenting patient care and battling healthcare understaffing.

AI to Help Detect Cancer

The combination of medical computers and AI to detect cancer could be a gamechanger for healthcare facilities across the globe.

A study by the University of Surrey and the University of California tested the use of AI networks and their efficacy in not only analyzing cancer symptoms from patient records, but also in using that data to identify cancer symptoms in patients that may have otherwise slipped through the cracks.

The idea is that the AI is constantly using a stream of live data from all connected hospitals and research centers, so its database is always improving. This information comes from a host of devices and locations — it combines demographics information, doctor notes on their medical computers, test results, lab images, examinations, Internet of Medical Things devices, medical surveys, study data, and any and all available recordings.

The AI then uses this information to create a kind of map of cancer symptoms. For instance, with access to such a firehose of information, the AI can use determinators like age, gender, location, previous medical history, genetics, and combine it with any known risk factors and symptoms. The AI can then compare all the data for that individual patient against ALL patients, everywhere, to determine the likelihood that the patient in question may have cancer, what kind of cancer, and how best to treat it.

Though this kind of AI network is still in testing, it could provide unprecedented levels of aid for diagnosticians, helping to catch cancer long before a test would normally be ordered.

It could even look at a patient’s risk factors and determine that they may just be at a high risk of cancer in the future, which could aid doctors in creating a plan to prevent that diagnosis in the future.

Paving the Way for AI

Artificial intelligence is already on the way, and could provide a quantum leap forward in diagnosis, patient engagement, and accessibility. However, AI definitely can’t do any of that on out-of-date or consumer-level technology.

Contact Cybernet today to learn about how long-lasting medical computers can survive and thrive in the brutal environment of a hospital, and how they can future-proof any healthcare facility for the bevy of technological changes that are on their way.

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.