The healthcare industry is being steadily transformed by artificial intelligence (AI) and machine learning. Just as AI is reshaping several industries, so too it is bringing new opportunities, and risks, to the world of MedTech. The potential spans from deep learning and neural networks in drug discovery, to the growing sophistication of AI-enhanced diagnostics and surgical robotics.

Throughout the history of health care, there are examples of technologies aiding doctors and helping patients to feel better or stay healthy. AI is now another one to add to the list, but something that makes it stand out is the broad range of possible applications. The examples I mention below offer a glimpse of what AI can offer, but there are certainly even more ways to use it — some of which are still undiscovered.

Healthcare and Med Tech are complex industries, so it can be difficult to figure out where to begin when utilizing AI, but it is critical that organizations understand how they can utilize the capabilities of AI and machine learning. AI has the potential to restructure workflows in various industries, saving people time and money, and when applied to the MedTech sector; AI can also save lives. Here are five ways medical technology companies can begin implementing AI into MedTech.

1. Improving the prediction and management of chronic conditions

Being diagnosed with a chronic illness can drastically change the course of a patient’s life. But, knowing things like how to manage the disease and how fast it’s likely to progress can improve a patient’s quality of life. Numerous examples of using AI to achieve those feats are underway.

Some of the options for using AI to diagnose are still being tweaked in labs and not ready for widespread use. Still, the preliminary results are impressive and might soon permanently change the steps physicians go through. For example, researchers have built a machine learning model that predicted the progression of diabetic kidney diseases which could predict the likelihood of progression with 71% accuracy.

2. Increasing Patient Compliance

When a patient doesn’t follow a doctor’s orders, they may be at an increased risk of complications, including hospital readmission, disease reoccurrence, or prolonged symptoms. AI could play a major role in encouraging patients to behave accordingly to a physician’s instructions. For example. through detailed home care instructions and contacting the person later to find out if they encountered any difficulties with the instructions.

In a study of stroke patients who were prescribed anticoagulant medication, an AI monitoring system raised adherence by as much as 67%. The more technology is leveraged to customize treatment, the less likely issues of patient compliance will arise.

3. Device Failure

Arguably the best use of AI in MedTech is predicting when a device will fail. Determining the lifetime of medical instruments and devices allows you to see when a device is at risk of failure. When you are working with potentially life-saving technologies, it is crucial for healthcare providers to be able to trust the equipment they are working with. By utilizing AI, you can have a better idea of when a device will need to be fixed or replaced.

4. Enhancing Telehealth Capabilities

The telehealth industry improves access to care, especially since the COVID-19 Pandemic, or when a person may live in a rural area and be 45 minutes away from the nearest medical clinic. In these cases, a telehealth app allows a patient to see a doctor via a smartphone or computer.

Some experts believe the combination of telehealth and AI could increase human potential by giving doctors more information that they can use to get to the bottom of a telehealth patient’s disorder.

5. Accelerating Drug Discovery Methods

The progress made in the health care sector regarding pharmaceutical drugs is often disconcerting to people who are waiting on new medicines to become commercially available while enduring situations where the product may prove lifesaving.

Many individuals who don’t have healthcare backgrounds often don’t realise the stages a new drug goes through. For example, researchers must figure out which formulations of a drug treat particular symptoms most effectively. Also, years may pass before a medication reaches a human trial phase.

However contrary to the excitement and innovation of AI, data, privacy issues, and ethical usage of AI must be considered. Some of the ethical concerns surrounding AI must be asked:

Who would be held accountable for machine errors that can lead to mismanagement of care?
Would patients be informed of the extent of the role AI is playing in their treatment?
Could healthcare practitioners feel threatened by AI about a potential loss in authority and autonomy?
It is evident that AI is a technology that can have a major part to play in the promise of affordable healthcare, improved success rates, efficient clinical trials, and a better quality of life. However, AI is such a buzzword currently surrounded by hype, and it is important to realize what helps and what doesn’t. While artificial intelligence is far from eliminating human involvement in the healthcare sector, it’s clear that it is already making a huge impact within the industry.