4 Unique Ways A.I. Will Affect the Healthcare Industry

No industry is immune to the impact of A.I. Whether you work in healthcare or manufacturing, you are a truck driver or pilot – artificial intelligence will soon enough affect the way you approach your day job.

And this is a fact we can all embrace.

For A.I. brings a wealth of opportunity in its efficiencies. Moreover, in fields such as healthcare, the potential for improved levels of service thanks to machine learning, clinical image analysis and other digital enhancements suggest we are on the cusp of a revolution.

Data-Driven Treatments

Big data is redefining industries across the spectrum; nowhere more so than in healthcare. A computer’s ability to analyse swathes of data is helping to expedite drug innovation, as test analyses become ever more involved.

As our understanding of individual treatments increases, doctors can prescribe courses of medication with more confidence, improving a patient’s rate of recovery considerably.

Evolved Understanding

An ongoing concern in healthcare revolves around a lack of understanding of neurological trauma or the potential long-term effects of brain damage. There are pockets of research, however, looking to combat such instances through smart algorithms assessing a patient’s ‘brain age’ following a violent shock.

Imagine the impact of a car crash – the associated trauma can be hard to determine yet have devastating effects on all involved. If we can leverage computer power to assist in diagnosis then prognosis, doctors will have a much clearer path to treatment recommendations. They can also flag increased risk of later-life neurological conditions, such as dementia.

In turn, they can take actions to slow any possible decline.

Automated Staff Management

One of the most prominent challenges to afflict the healthcare sector is staff shortages. Ensuring that a hospital has sufficient coverage to deal with ensuing events is incredibly complex, with many inefficiencies across the board.

Artificial intelligence and automated staffing solutions allow organisations to operate on a dynamic model. That is, they staff up at times when they know there could be increased patient care demand, while they also allow the unrequired resource to attend other hospitals or clinics when demand drops.

Such flexibility guarantees an optimum model by which to use staff time, mitigating shortages.

Predictive Treatment

A further application of A.I. lies in predictive medicine. Heart disease is a common cause of death in patients of all ages. However, predictive modelling is proving a robust approach to determine death risk and, thus, plan preventative measures for those deemed in most danger.

For example, a virtual 3D render of the heart can plot how the organ beats, with machine learning, MRI and other medical testing determining the presence of previously unobservable risks.

Interestingly, magnetic resonance is finding other powerful applications, particularly in the field of MBST therapy. MBST is a non-invasive therapy with no known side effects since studies have indicated that patients suffering from pain associated with osteoarthritis have reported a reduction in pain levels post-therapy. Other clinical studies have shown an increase in bone mass density after Magnetic Resonance Therapy.

Thus, it is not only the predictive systems that will benefit the broader population but technological innovation on a wider scale that will be truly revolutionary.