Nowadays, Artificial Intelligence (AI) is used in many different fields, such as finance, automobile, education, gaming and many more. In spite of the fact that they are all very essential and useful, AI is estimated to have the greatest impact on healthcare in the future. What’s more, there are many favorable factors that contributed to the development of AI in this field. One of them is the access to large amount of data, which in this case is crucial. All medical appointments, medical history, health information or prescriptions are registered in our accounts, which gives a lot of possibilities for implementing AI. Another factor is the use of complex algorithms, especially development of deep learning and neural network.
Deep learning is a subset of machine learning, so we can say that it’s ‘more advanced machine learning’, which tends to work like human brain. By using the available data and a multi-layer structure called artificial neural network, deep learning make it possible to work and draw conclusions similar to the human brain by constant data analysis.
How exactly is Artificial Intelligence used in healthcare?
Medical data management
AI turned out to be very helpful for many medical organizations if It comes to supporting data management. The AI-based robots are used to collect, analyze and store data, which provide fast flow and constant access to the information. Some of them are able to predict the user’s intention and, moreover, they help doctors make decisions and, in some cases, take actions.
Diagnostics
Thanks to the wide possibilities of data analysis and processing, deep learning is implemented in the area of diagnostics. Neural network is able to detect cancer cells or analyze MRI scans in detail. A special neural network called VoxelMurth (convolutional neural network) is used to analyze the MRI images-it is a very difficult process which requires large database and often takes many hours.
AI in early detection
If we look around, we can see many people wearing modern devices, including e-watches. For many, they are just a gadgets that make life easier, but it’s worth noting that they often have advanced health monitoring features. AI-based health trackers, like Fitbit, Garmin or Apple Watch, are able to collect and analyze data such as sleep cycle, activity level, heart rate or blood pressure, which can e.g. predict heart attack.
Of course, we have to take into account the fact that at this stage AI is not able to work independently and completely replace doctors and medical staff. However, looking at the rapid development in this field and the incredible potential of AI, we can assume that it will significantly change the medical industry.
Sources:
Artificial Intelligence In Healthcare | Examples Of AI In Healthcare | Edureka – YouTube
What is Deep Learning and How does it work? | Towards Data Science
AI is Improving Healthcare… But Will Benefits Be Widely Shared? (gettingsmart.com)
Many people believe that in future AI and robots will completely replace doctors and even do operations on people. Even now a lot of doctors use some kinds of robots or mechanisms which are able to make accurate calculations and actions, which eliminates the human factor which could play a big role and influence the result of surgeries and decisions on medical treatment. However, it may arise the problem of employment, as doctors may become useless compared to AI at some point.
AI may indeed replace doctors and operations, which is quite scary to be honest. It is going in that direction very rapidly. Not long time ago, Polish doctors from a hospital in Lublin participated in an operation from distance, that took place in Bulgaria. It is important to state that this is the first in Poland and one of the first in the world distant operations and was possible only due to advanced visualisation techniques and use of hologram. The doctors that were 1,5k km away from each other were collaborating while operating 61 year old man with AAA (abdominal aortic aneurysm). Quite impressive, don’t you think? And that is just the beginning. What’s next?