Machine diagnosis may become the norm in the future.
Doctors can look at X-ray images and analyse what they see. Thanks to their expertise, they can diagnose a patient’s health simply by looking at these images.
We are already at the stage where this type of expertise can be stored and automated. With a large number of already classified X-ray images, an artificial intelligence can be trained to diagnose diseases. Thanks to a significant scientific breakthrough called deep learning, there is no need to tell the AI what parts of an image led to the diagnosis; it can discover the diagnostic rules itself.
AI to solve healthcare labour shortage?
“Healthcare is one sector that will see a significant change thanks to artificial intelligence. Work in this field has traditionally required expensive knowledge, but now part of that knowledge can be automated”, says Professor of Practice Leo Kärkkäinen.
He believes that medical diagnoses by machines will be commonplace in the future. Automating repetitive and time-consuming work can help free up expert resources for more demanding tasks in a sector that is plagued by labour shortage.
Kärkkäinen has participated in a research project for detecting subarachnoid haemorrhages. The arachnoid membrane separates the brain tissue from cavities in the brain. When a blood vessel in one of these cavities starts to leak, no typical neurological symptoms of a brain haemorrhage may appear, except for a severe headache. In most cases, patients are X-rayed, but there is not always a radiologist present to detect possible leaks in the images. This is where a diagnosis made by an artificial intelligence could save a patient’s life.
“This is AI application at its best. An artificial intelligence does not necessarily do things better than a human, but it can work faster and regardless of the time of day, which is perhaps its greatest advantage”, says Kärkkäinen.
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