Chat with us, powered by LiveChat
​How is Artificial Intelligence and Machine Learning Transforming Medical Devices?

​How is Artificial Intelligence and Machine Learning Transforming Medical Devices?

The medical devices industry in the United States has seen immense growth over the years and it’s an area of innovation as well. Manufacturers and researchers always seek new opportunities to integrate automation with accuracy and make different devices more usable with least human intervention. Take ekg machines and ultrasound systems, for instance, new technology has continuously been introduced to transform the medical devices of the future.

Before we get into the details of how medical devices are being transformed through AI and ML, let’s first understand the two technologies.

What Is Artificial Intelligence?

Artificial Intelligence is the science of engineering intelligent machines, particularly intelligent computer programs. It is all about making smart machines that are capable of doing tasks which generally need human intelligence. It is based around models that work on statistical analysis of data, machine learning, and expert systems which primarily work with if-then statements.

What Is Machine Learning?

It’s an AI technique which is used for designing and training software algorithms to self-learn from data and act on it. Both ‘locked’ and ‘adaptive’ algorithms can be developed using machine learning depending on the needs of the application. Generally, the idea is to make programs that learn and change their behavior based on data collected over time.

The real-world examples of AI and ML use in medical devices can be:

  • An imaging system which uses algorithms for giving diagnostic information for the patients of skin cancer.
  • Smart EKG machines that are capable of estimating the probability of heart attacks.
  • The Latest Trends In Artificial Intelligence For Medical Devices

    Recent research suggests that the current emerging AI applications can be part of three major categories.

    Chronic Disease Management – Manufacturers are leveraging machine learning for monitoring patients with the help of sensors and for automating treatment delivery through connected mobile applications. For instance, automated delivery of insulin to patients with diabetes.

    Medical Imaging – AI-driven platforms are being integrated in medical scanning devices like MRI machines and CT scan machines for improving image clarity. It helps improve clinical outcomes as the radiation exposure is reduced. An example could be GE Healthcare CT scans for kidney and liver lesions.

    Artificial Intelligence and Internet of Things – Medical device manufacturers are integrating Artificial Intelligence with IoT for better monitoring adherence of patients to the treatment protocols and to achieve better clinical outcomes.

    The Future of AI Technology In The Medical Devices Market

    The constant effort towards making more reliable and accurate medical devices is garnering a growing interest in coming up with new ways to integrate artificial intelligence and automate things in the future. The area of medical imaging has already started gaining traction and the clinical valid wearable devices have started emerging to the scene as well. The major focus, however, will be towards making and improving medical devices that support the treatment and management of different chronic illnesses.

    As the American live longer, identifying new and innovative ways to manage care in the older adults is going to be increasingly important in the future. And, as patient adherence to the treatment is a major challenge in the management of chronic diseases, some big healthcare device manufacturers are working on automating the process of administering medication to the patients. Shifting this adherence responsibility to an automated, reliable medical device would mean an improvement in life quality.

    Surgical robotics might also see an implementation of AI and Machine learning in the future. Combining them with Augmented Reality, tumors could be highlighted during surgery and the robots might then be allowed to do some type of a close up in the end. Integrated sensors might also be developed to look through those thin tissue layers and stop the surgeons’ hands from coming close to areas that should be avoided or aligning the pedicle screw while the surgeon tries to co-align it with their expertise and training. The implementations could be endless.

    Looking at the future, a couple of trends are expected to be predominant:

  • Medical devices introduced with AI and VR integration, and
  • AI devices converting to meet the needs of medical applications.
  • Even today, AI has become quite commonplace in the modern medical devices. However, a major consideration for the manufacturers, regulatory agencies, and the clinicians looking to implement these devices is how efficacy and safety are demonstrated. Nevertheless, huge progress has been made in this area and things will continue to improve. 
    Nov 30th 2020 Jaken Medical

    Recent Posts