Guest blog: AI as an enabler in healthcare

Organisations all around the world, both in the private and public sectors, are adopting Artificial Intelligence (AI) to provide more scalable and faster services, while also saving on budget and man-hours. This is no different in healthcare AI, which is a prime example of how technology is being used for saving and improving people’s lives. From automation in the central sterile supply department at hospitals to the smart watch on your wrist, Industry 4.0 has reached unprecedented levels when it comes to health.

Robot surgeons and virtual nurses

In the last few years, robots have proven to be great resources in the operating theatre. One popular example is the Da Vinci, currently the most advanced surgical robot in the world, which allows doctors to perform complex surgeries and have greater precision, while carrying out minimally invasive procedures. There is also a study published earlier this year which reviewed 379 orthopaedic patients and showed that procedures assisted by AI had five times fewer complications compared to surgeons operating alone.

Another technology that has been getting much attention recently (especially for its cost-saving qualities) are virtual nursing assistants, which help to reduce unnecessary hospital visits and save medical professionals’ hours. Angel, for example, is a bot from a company called Care Angel and allows for patients to perform wellness checks through voice AI; being able to manage, monitor and communicate health data.

Big data and healthcare walking hand-in-hand

On the big data side of things, there is the possibility of taking data from a very large group of people and understanding the likelihood of certain outcomes and taking the appropriate proactive action. It would be possible to run machine learning over large data sets of knowledge about patients and clinical outcomes, where it would show, for example, that people at a particular group would be much more likely to suffer from diabetes when they’re older, therefore will need an early intervention to stop that from happening. Another use for early detection is the use of AI in mammograms: the technology is enabling mammogram test results to be reviewed faster and with 99% accuracy – which again, saves on costs and man-hours by reducing the growing problem of unnecessary biopsies.

At the other end of the spectrum, many of us now have smartwatches and wearables. These devices know a lot about what kind of exercise a wearer is doing, the current state of their heart health, logged food diaries and so on. This data, when coupled from knowledge from your GP or hypothetically shared with an application that the NHS might make available, could send you notifications to suggest that you might want to go see their GP and talk about a possible condition.

Smartwatches are not only appealing to the young crowd, but elderly people (and their families) are also keen on benefitting from their many healthcare elements. The new Apple watch, for example, has many relevant features to senior citizens and caregivers, such as high-precision, FDA-approved heart monitoring and fall detection. The latter allows that emergency contacts stored on the elderly person’s iPhone be contacted in case they suffer a hard fall, which is done thanks to the device’s sensors and the data analysis from wrist trajectory and impact acceleration.  Smartwatch-friendly apps such as “Alert”, which allows people who need assistance to contact a caregiver for help by pressing a button on their wearable, are also great additions for the growing senior population adopting AI in their everyday lives.

No doubt, there is still a long way to go when it comes to maximising the use of AI and making the most of it, however, there is still infinite potential to explore and apply the technology we currently have to revolutionise Healthcare, both in the public and private sectors; including on a personalised, individual basis.

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