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Artificial Intelligence in Medicine

By Michael Maccallam

Artificial intelligence has long been the fascination of scientists and filmmakers alike, whether it has been through apocalyptic visions or dreams of utopia.

However, despite people’s beliefs that the creation of artificial intelligence would be welcomed with breaking news headlines, forms of AI have already been introduced into many fields of work, including medicine.

Although many doctors will say that their knowledge is based solely on their years of rigorous education, many will also say that it has been their past experiences and judgements that have led to the level of expertise that they work with – things which are far less tangible and far more difficult to measure.

Therefore, with the medical field seeming highly subjective, it would make sense that this would be an almost impossible area for machines to infiltrate, but this seems to have been proven wrong.

In the era of modern medicine, doctors have found themselves increasingly dependent on countless studies and different drug options, which is limited to the human capacity of the doctor’s mind. The use of machines, however, eliminates this problem, since a machine is not limited to the same boundaries as the human mind. Alongside this, artificial intelligence would be able to interpret and analyse a patient’s data and instantly be able to offer the best diagnosis and drug choice.

The issue must not be seen in terms of taking the doctors’ jobs though. On the contrary, artificial intelligence is increasingly being seen as a necessity rather than an option, since it seems counter intuitive to base a diagnosis solely off the opinion of the doctor when a much more reliable source is so readily available. This branch of artificial intelligence has been named machine learning by many, with the idea that just like a doctor, the machine itself can learn and develop new methods of diagnosing patients.

Not only could this emerging technology revolutionise physical health though, it also has significant implications for mental health. Such ideas include exploiting the relationship we all have with our smartphones nowadays, whereby a mobile phone will be able to monitor the interactions that the user makes, detecting any signs of depression or bipolar disorder that may be visible from their posts on social media or their searches on the internet.

David Ahern, of the Department of Psychiatry at Brigham, has said that ‘historically we have been dismally poor at detecting dangerousness or self-harm’ and that ideally ‘we may be able to develop an early-warning system that […] could monitor and see changes in patterns to better determine when the risk gets to the level where intervention is needed’. This system would be able to detect how mild or aggressive someone’s illness is and would offer more reliability than that of a doctor.

Ultimately, this technology is still in its inception, but there is little doubt among medical professionals that this area of artificial intelligence will go on to pave the way for a new era of medical science.

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