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How Is Artificial Intelligence Used In Medicine?

Artificial intelligence has had a broad application of uses in recent times across a multitude of industries. It’s extremely efficient, with automated processes and machine learning assuming the more menial roles usually manned by humans. Now, all the tedious admin and ‘busy work’ can be funnelled through a machine for efficient and consistent results.

But is AI used the same way in medicine, or is it utilised for other purposes too? What roles does it take on, and what is it responsible for? Is it always a good idea to use AI where doctors and nurses would do?

Consequently, here’s how artificial intelligence is used in medicine.

AI’s medical uses

Doctors are far from dependent on AI technology. Obviously, all the latest tech is incredibly expensive, and won’t be subject to widespread or regular usage for some time, if ever. Currently, AI is used sparingly for the sake of accuracy and precision, rather than to allow hospitals to run before they can walk.

But what is AI currently used for? Well, through medical imaging, it can reportedly help doctor’s more easily spot and treat lung, skin and ovarian cancers, diagnose up to 50 eye conditions including age-related macular degeneration, and further diagnose relatively newly discovered diseases like atrial fibrillation, which causes the heart to beat erratically. There’re even opportunities with things like AI therapy. Still, AI is only useful so far as the data it collects, using its algorithms to spot patterns in patient scans and then drafting results, which makes it’s uses helpful yet limited too.

Moreover, it also has great uses in the areas of data management and patient records. It can gather data from patient interviews and manage things like follow-up appointments. This frees up time for specialists and doctors to be more productive in the way of treatment and diagnosis, instead of paperwork. This can put doctors on task sooner and may even improve patient flow if patients are diagnosed, treated and wheeled out of hospitals quicker.

Energy and power

In terms of energy, obviously AI is entirely dependent on power to function. While things like dc power supplies can always help, if there’s any disruption to services in the events of widespread power cuts, cyberattacks or breakages, hospitals are obviously in a critical level of trouble. Therefore, it’s probably best that AI is used a supportive tool, and not the driving factor in diagnosing and treating patients. After all, the NHS has been hacked before; if AI takes centre stage, the consequences of such attacks or faults can be far more severe.

Power plays an important role in AI’s functionality in other ways too. In terms of power as influence, the NHS has recently invested in their very own AI lab, with the Health Secretary Matt Hancock stating that AI had “enormous power” to improve care, save lives and free up doctor’s schedules so that they can fit in consultancy and one-on-one periods with their patients.

As previously mentioned though, AI is only as useful as its accumulated data allows it to be. Given that much of the world’s medical research has been conducted on those of white ancestry, there’s also a power imbalance in terms of race too. Unfortunately, this means that AI may not be as effectively useful to those of different ethnicities. Ultimately, this glaring power imbalance needs to be addressed quickly so that these technologies can work in favour of all.

Written by Nat Sauteed

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