Artificial Intelligence and big data are more commonly used in healthcare every year. With this article, we will take a closer look at both these disciplines and see the benefits of implementing Artificial Intelligence and big data in the healthcare industry. We will also go through the history of Artificial Intelligence and big data in healthcare and its future.
Similarly, as in the pharmacy – Artificial Intelligence is a new trend in the healthcare industry sector and you can easily say that it’s still in its infancy. When most people hear “Artificial Intelligence in healthcare” their first thoughts may be related to the Star Wars movies, where there are no human doctors. Everything related to healthcare is done by intelligent robots and systems. Is this our future? Well, probably. But we are still far away from that. Let’s stick to the Earth!
What is artificial intelligence in healthcare?
We should start at the beginning! What is artificial intelligence in healthcare exactly about? Take a look at the definition provided by Wikipedia: “is the use of complex algorithms and software to emulate human cognition in the analysis of complicated medical data. Specifically, AI is the ability for computer algorithms to approximate conclusions without direct human input”.
To put it in more “human” language – Artificial Intelligence is everything including applications, systems, algorithms and devices that help human physicians in providing healthcare and is based on computer analysis and big data. For instance: robot-assisted surgery units, diagnostics algorithms, drug research algorithms, devices monitoring patient’s body condition and many more. It is hard to imagine modern medicine without additional artificial intelligence support, even though the way to its real role in the healthcare industry has “just” started. So long story short: what is artificial intelligence and big data in healthcare? It’s a necessity!
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History of AI in healthcare
History of Artificial Intelligence in healthcare is quite short as it needs many modern time inventions to work, to name just computers and the internet. The first attempts to implement Artificial Intelligence in healthcare were in the late XX century around the 1970s when Dendral was introduced at the Stanford University, USA. It is assumed to be the very first Artificial Intelligence in the healthcare system. Originally it was used to help chemists in identifying unknown organic molecules, by analyzing their mass spectra and using knowledge of chemistry. Dendral was written in the LISP programming language and was a father for many following Artificial Intelligence systems in healthcare, to name just the MYCIN – system that used Artificial Intelligence to identify bacteria causing severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the dosage adjusted for patient’s body weight.
The next milestone happened in around 1990 in the minds of the artificial intelligence systems. They decided that if AI has to offer any assistance it has to be based on the expertise of physicians and take into consideration the lack of perfect and vast data. That was necessary for the following development and improvements of artificial intelligence in healthcare. Since then much has changed and today Artificial Intelligence in healthcare is much more advanced.
Examples of artificial intelligence. How is it used today?
Today, Artificial Intelligence in healthcare brings much more value to the industry. It is developing rapidly and is predicted to do so, or even faster in the near future. We will take a look at the future of AI in healthcare, but first, let’s find out what goes on right now.
Take a look at some examples of how is Artificial Intelligence used in healthcare and check what benefits Artificial Intelligence brings to the healthcare industry.
Examples of Artificial Intelligence in healthcare
One of the examples of Artificial Intelligence in healthcare is diagnostics. We wrote about that previously in the article about AI in pharmacy. Diagnostics consist of tons of data – to name just medical imaging analysis, patient medical records, patient treatment history, patient genetics, and his or her circumstances.
In the past few years, AI has become more accurate in identifying disease diagnosis and recommending optimal treatment. The best example is the cancer diagnosis. Standard, radiological methods are not sufficient. As it turns out, traditional radiological imaging misses signals indicating cancer in about 30% cases! On the other hand, Artificial Intelligence is much more accurate. In 2013 data scientists from the KAIST University in South Korea introduced an Artificial Intelligence algorithm called LUNIT, that’s capable of identifying cancer cells basing on x-rays images and mammography images to detect lung and breast cancer. Its accuracy was mind-boggling 97% in detecting lung cancer and breast cancer.
According to the Accenture company, automated image diagnosis itself can save a whopping $3 billion a year!
Take a look at another example of Artificial Intelligence in healthcare – robot-assisted surgery. This is one of the most essential applications of Artificial Intelligence in healthcare. In this case, there are two main benefits – huge money savings and more effective surgery. Accenture estimates that AI robot-assisted surgery could save the US healthcare industry $40 billion annually by 2026.
And what about the surgery itself? Well, as we said, robot-assisted surgery is much more effective and precise. In 2017 alone there were executed almost 700 000 robot-assisted procedures. Thanks to its precision and miniaturization, the results are undisputable – smaller incisions, decreased blood loss, less pain, and quicker healing time. However, there is the other side of the coin. The robot-assisted procedures are more expensive, as one robotic unit costs at least $1M, and it takes time to properly train surgeons in using Artificial Intelligence support. Surgeons have to perform 100-250 surgical procedures in order to use their new robot assistants with the benefit of the patient*.
Now you know how is artificial intelligence used in healthcare. Let’s turn to the big data.
Big data in healthcare
Although big data in healthcare is strictly related to Artificial Intelligence in healthcare, these two disciplines are not exactly the same thing. To simplify it, think of big data as a source for Artificial Intelligence. Big data is exactly what powers up the Artificial Intelligence and allows it to work efficiently.
When you deal with large amounts of data, at some point it becomes very difficult or even impossible to master all of those gigabytes. The data scientists are trying to automate the storage and analysis of these large amounts of data in order to get as many advantages as possible from them.
Big data in healthcare consists of billions of entries about patients, treatments, drugs, surgical procedures, research results, and many more. If you want to use all that data on a regular basis, you simply have to think of the way to analyze and process it efficiently. And this is what big data in healthcare is about.
Now, take a look at the benefits of artificial intelligence and big data in healthcare. Generally speaking, big data can help in improving patient service, determining and implementing appropriate methods for patient treatment, supporting clinical treatment or monitoring efficiency of the healthcare companies. There is much more, but today we will name and look closer to the three most important benefits.
Benefits of Big Data in healthcare
1. Much more improved patient care: thanks to the electronic data records, collecting patient data is much more effective and easier to use to find the best treatment for the given patient. Big data helps in collecting demographic and medical data such as lab tests, clinical data, diagnoses, medical conditions, treatment history, family member’s clinical data, etc. What’s more, big data can help in the prediction of disease incidence or detecting trends that lead to better health and lifestyle of society.
2. Improved operational and R&D efficiency. Healthcare companies can cut down on healthcare costs and provide better care. All that with the help of predictive analysis of the staff efficiency and patient admissions for example to the hospital. Big data in healthcare helps in organizing workflow and provide not only better care but also more effective in terms of the costs. And what about R&D? Big data is supporting work on new drugs and clinical trials thanks to the ability to analyze all data instead of the selection of the test samples. Big data also has the ability to identify specific patients with wanted biological characteristics who will participate in specialized clinical trials.
3. Finding a cure for diseases. Big data can help in uncovering earlier unknown disease correlations, hidden patterns, and insights. All thanks to examining large sets of data to find new cures for the diseases or prescribe the best treatment. Big data has the possibility of predicting the occurrence of specific diseases or prognosis of disease progression and factors determining it.
Surely, you will agree that the benefits of big data in healthcare are staggering, creating great new possibilities and perspectives for the future.
Future of artificial intelligence and big data in healthcare
Now you know what big data and artificial intelligence look like currently and how they are helpful in modern medicine. What we should do now is to concentrate on the future. What future of artificial intelligence and big data in healthcare is going to look like?
Because artificial intelligence is producing great savings (it is estimated that by 2026 it will save up to $150 billion!). Its development will definitely go on. Firstly, we go back to the question from the beginning of this article – will machine doctors replace humans? It is probable. Actually, it happens already – for instance there is almost no need for human presence in radiology! Artificial algorithms are much more accurate in their judgments and above all – noticeably faster. When it comes to human life, time is the most important factor. Just seconds can change everything. So we expect to see a much bigger role of artificial intelligence in a diagnosis.
Another thing – AI systems are “armed” with a lot of information so they can assist in clinical decision making. And their role in that part of medicine will go sky-high in no time. The minimization of diagnostic errors and therapeutic errors are the most obvious results. Future doctors will base their work and judgments almost entirely on artificial intelligence.
To sum up this part we might say that the future of artificial intelligence and big data in healthcare is full of great perspectives and fantastic potential!
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That happens already, but shortly they will be much more advanced and complicated. Imagine Google Assistant telling you it is time to do your blood tests. Or even doing these tests by itself through your smartwatch. Healthcare apps will be something more than they are now. They will act as a personal health assistant, keeping you updated about everything going on within your body. That will considerably shorten treatment time and lower its intensity. As it is well known that the faster you detect the disease, the easier it is to cure.
These are just a few examples of what the future of artificial intelligence and big data in healthcare may look like. The physician of the future will only have to supervise the work done by the AI algorithms and robots. And maybe in a much longer time, there will be no need for a human physician? Just as it was in the Star Wars movies. Time will tell.
We hope that you enjoyed exploring the world of Artificial Intelligence and Big Data in Healthcare. We would love to hear your thoughts. Maybe there are some issues that you would like to learn more about? Let us know!
- Source: “New technology and health care costs–the case of robot-assisted surgery”. The New England Journal of Medicine.