Artificial intelligence has long been a standard in science-fiction, but reality has brought this technology to life. AI-based medical devices are not quite at the level we’ve seen in books or movies, but it is accelerating at an incredible rate. It’s easy to imagine AI in fields like electronics manufacturing or automation, it’s more difficult to see such technology in charge of our medical devices.
After all, these devices can mean life or death to those using them, which leaves no room for error. Can we really trust an AI to assist with the manufacturing and maintenance of our medical devices? Trust is only the beginning, but if we embrace this concept, it could revolutionize everything about the medtech industry.
AI in Medical Device Manufacturing: Where do We Stand?
According to the FDA, any device that utilizes machine learning, neural networks, or natural language processing falls under the category of artificial intelligence. Of course, we’ve been using AI for some time now to handle menial tasks like handling records or medications, but now things are taking another step forward.
The applications are numerous, but the FDA, along with the greater populace, will need more proof before they allow AI to handle their medical diagnoses or treatment. In the United States, medical devices have been regulated by the FDA since 1976. The organization has managed to keep up somewhat with new action plans and guidance, but this doesn’t stop bottlenecks from forming.
Meanwhile, in Europe, new regulations emerged in April of 2017. However, there doesn’t exist any specific regulations to help AI-enabled devices into the market. Ultimately, the regulatory bodies have long struggled with keeping pace as new technologies emerge.
In our digital age, privacy is also a major factor. How can we ensure that information captured by these devices doesn’t fall into the wrong hands? The industry as a whole continues to struggle with classifying, quantifying, and safeguarding these devices from data theft.
Combined Efforts to Integrate AI and Medical Devices
In spite of these obstacles, there are already some exciting ideas developing between healthcare and AI. A partnership between University College London Hospitals (UCLH) and the Alan Turing Institute, for example, has brought AI into the National Health Service (NHS).
The goal here is to leverage machine learning algorithms for the purpose of identifying critical triage patients. Similarly, the Canadian government has also approved licenses for AI innovations that include 14 regulatory recommendations that intend to incorporate AI into the country’s healthcare system.
Combine this with efforts from major companies like Freenome, Raysearch, IBM Watson Health, and efforts from Microsoft’s Project Hanover or Google’s Deepmind, and the foundation is here. We simply need to combine global efforts with regulatory developments to allow the transition into the future of medtech.
Upcoming Innovations and Applications
The current trends point to three major applications for AI-based medical devices: managing chronic illness, improving medical imaging, and patient monitoring. In keeping with these goals, here is a look at some companies that are pushing products that integrate artificial intelligence and medical applications:
This medical device company is tackling diabetes, which is a chronic illness that affects over 30 million Americans. Their first solution is the Sugar.IQ app, powered by IBM Watson. The app delivers personalized messages regarding glucose patterns. It also follows specific actions or foods to learn more about the impact it has on the patient.
The app also tracks food and provides dietary insights to help assist users with properly balancing their glucose levels. The company also launched the MiniMed 670G system. It automates the delivery of insulin based on algorithms that are trained to self-adjust delivery every five minutes.
2. GE Healthcare
In late 2017, GE and Nvidia announced a partnership to bring the latter company’s AI platform to GE’s 500,000 imaging devices currently on the market. The goal is to leverage AI to improve the speed and accuracy of computerized tomography (CT) scans.
In addition to streamlining the process, algorithms can be trained to look for intricate patterns that doctor’s may miss. This could lead to smarter diagnoses and better treatment.
3. Philips Healthcare Combines IoT and AI
Among these innovations, wearables are a major area of growth. Philips Healthcare recognizes this potential and seeks to utilize the technology in their IntelliVue Guardian Solution. This patient monitoring system utilizes AI to predict when a downturn in a patient’s vitals may occur.
According to Philips, the system combines software, support algorithms, and mobile connectivity to make the entire concept possible. Doctors can simply place a wireless device on the patient’s wrist and monitor their health remotely.
Looking to The Future
Artificial intelligence is making its way into all manner of industries and products. Whether it’s Amazon using it for Alexa, or Tesla harnessing the technology for self-driving vehicles, it’s clear that AI isn’t going anywhere. For medical devices and the way they’re manufactured, AI presents some exciting applications for the industry.
According to Todd Morley, director of data science at Medtronic, some of these uses include quality control, supply chain optimizations, and predictive maintenance. Ultimately, quality control seems to be one of the most effective uses of this technology.
It doesn’t take much time or effort to imagine the implications of a faulty medical device, which is why substantial amounts of time and resources are devoted to ensuring everything works properly off the assembly line.
AI and Medtech: The Main Takeaways
A combination of machine learning algorithms and predictive analytics allow software to identify variances or discrepancies with incredible accuracy. The AI-driven solution is then able to alert the proper individuals and stop the problem before it starts.
Pair this with IoT systems that leverage cutting-edge sensors and the amount of data available to you increases exponentially. When you boil it all down, these are the main takeaways:
- AI-based medical devices are here to stay. Embracing it requires a long-term commitment and an understanding that you’ll need to continuously improve the solution as new options become available
- Machine learning algorithms are only as good as the data provided to them. Take a look at where and how you source your data, and look for ways to enhance that suite of information to empower your AI-based solutions
- Start with your goals and work backward. What do you hope to accomplish, and what do you need to make it happen? Asking these questions will help you better understand what AI can do for you and how to implement it properly
Artificial intelligence is just one piece of the puzzle. Above all, the entire industry is undergoing a digital transformation. All of this leads to better products, smarter solutions, and a bright future for the medical device industry.