Artificial intelligence could tap into the enormous volumes of data not only on our bodily systems and genetic heritage, but also on various pharmaceutical substances — and help physicians design our treatments individually.
Scientists including those from Aalto University and University of Eastern Finland have developed a new artificial intelligence (AI) technology that can compare different treatments and identify the most suitable alternative for a patient.
Why different treatments for different patients?
How a new vaccine, antidepressant or chemotherapy drug is absorbed is unknown, claims Aalto. Likewise, how it affects and lives in particular person’s body remains open.
To get through the data chaos and find answers, we would need to process superhuman volumes of information with even more superhuman speed.
The last time medicine treated people as individuals, our cures were leeches, mercury, and herbal mixtures, while the most fortunate found pain relief from opium.
As doctors engaged in trial and error, patients expired.
Traditionally, the effectiveness of medical treatments is studied by randomised trials where patients are randomly divided into two groups: one of the groups is given treatment, and the other a placebo.
Scientists showed that there may be other ways to evaluate treatment effectiveness.
Artificial intelligence is the ‘other way’
In the study published in the journal Healthcare Informatics Research, the researchers used the method to evaluate treatment effectiveness in obstructive sleep apnoea — a potentially serious sleep disorder in which breathing repeatedly stops and starts.
However, the method can also be applied to other treatments, researchers said.
The study showed that in patients with sleep apnoea, the continuous positive airway pressure (CPAP) treatment reduced mortality and the occurrence of myocardial infarctions and cerebrovascular insults by five per cent in the long term.
For patients with heart conditions, CPAP was less beneficial.
Similarly, associate Professor Tomi Laurila at Aalto University employs new carbon materials in the development of extremely sensitive sensors intended for measuring, for example, the concentrations of different neurotransmitters in the brain or the spread and effects of pharmaceuticals in the body.
How AI does it better
According to Professor Olli-Pekka Ryynanen from the University of Eastern Finland, the method opens up new and significant avenues for the development of medical research.