What is the Use of Artificial Intelligence and Robotics in the Healthcare Industry?
If you have a sincere interest like me in what artificial intelligence and robotics can do in the healthcare industry, you may want to read this article. Just like you, I am in search of answers to the question ‘why AI has become such a buzzword and why AI healthcare application development is at the forefront of technological development?’
A small statistic will make it clear where we are and where we are going. According to forecasts of Grand View Research, an India and US-based market research and consulting company, the global artificial intelligence in the healthcare sector will amount to USD 120.2 billion by 2028. This number was 8.23 billion in 2020, according to Allied Market Research.
If the forecast is not an exaggeration and is based on evidence (and most probably it is as Grand View Research is quoted by the world’s renowned academic institutions), it’s worth looking at the issue in more depth.
Let’s have a look at what AI can do in and for the healthcare industry and whether AI healthcare application development makes any sense at all.
Firstly, we will cover the good stories and illustrate all the benefits this innovative technology can bring to humankind. We will end the article with a question rising worries: ‘’who is liable for AI malpractice?’’ Keep on reading if this subject interests you as a professional or if you are someone who wants to be on top of world developments.
Below are some benefits of AI and robotics in the healthcare industry.
Massive Data Processing
The data that is at the disposal of hospitals and other providers is immense. The amount of data is so big that it is not possible to structure meaningfully without software. Thanks to the development of AI-driven applications like machine learning and data-mining technology, it is possible to comprehend the data with higher precision. The machines find patterns in the vast amount of data that would otherwise be unnoticed by the human brain.
AI solutions enable more accurate diagnosis through the personalization of medicine. Aiforia Clinical Suites is a perfect example of a health institution that is developing different clinical suites for the most prevalent cancers in the world, including prostate, breast, lung, and more. Aiforia equips pathologists and scientists in preclinical and clinical labs with powerful deep learning artificial intelligence software for better diagnosis and discoveries. The establishment aims to escalate the efficiency and precision of medical image analysis beyond current capabilities from oncology to neuroscience and more. The data-driven models increase the accuracy of diagnosis through personalized medicine with more precise data.
Artificial Intelligence and robotics have transcended geographical barriers. Today, AI-powered eHealth technologies enable monitoring of patient cases allowing better patient experiences while reducing the number of in-person visits.
The market is flooded with healthcare apps that are guided by high standards and AI healthcare application development requirements. The simplicity of apps and device compatibility contribute to better penetration of the technology. Today, you don’t need to visit a doctor for blood pressure or other parameters generated by monitoring devices.
A good example is Molly, a multi-functional virtual nurse. Patients with medical conditions such as diabetes or heart failures sign up to the site and the platform draws up a personalized care plan based on their medical records. The patients then have regular check-ins with the virtual nurse in between their appointments with the real practitioner.
Auxiliary robots are auxiliary equipment that help doctors at the hospitals. An excellent example is the UV Light disinfectant robot, which cleans germs from a hospital room.
However, the advancement of technology promises more than that. A current study on home-auxiliary robot systems promises to provide daily life assistance for people with physical mobility disabilities. It relies on simple actions like blinking or tongue extension to complete the motions of a mouse in the system screen. This innovation can drastically improve the quality of life of people with disabilities.
But being an Armenian, I can’t help but mention the first Armenian AI-based robot Robin that was recognized as the best innovation of 2021 by TIME magazine. Robin plays, answers questions, and entertains kids at hospitals. TIME tells the story of an 8-year-old child with pneumonia who refused to eat for two days. For about 20 minutes Robin played games, discussed the child’s favorite animals, and variously entertained the child. Then the robot left the room saying he would come back only on one condition — if the child would eat. After this, the child surprised everyone.
People get disabled for various reasons. Accidents happen, children with limitations are born, and most drastically — wars happen that leave lots of young people without arms and legs. The Prosthetic and Orthotic industry is the field of healthcare where the benefits of AI cannot be exaggerated. Today, various anatomical and biomechanical functions are stimulated by the neural network.
What happens is that the functional loss due to amputation, spinal cord injury, brachial plexus injury, or traumatic brain injury results in a loss of connection from the brain to extremity, and these extremities cannot function as a healthy limb. Today, prosthetics and orthotic devices or rehabilitation aids are used to replace the lost structure and functions of extremities.
Artificial Intelligence and Mental Health
Yes, we are talking of robots but it’s surprising today that AI machines can help people with mental disorders. And this concerns both the prevention, treatment and diagnosis of mental health. One thing is that new medicines are coming about as AI machines analyze and detect new patterns in voluminous data that could not be structured in any meaningful way by a human being.
As Forbes contributor Ganes Kesary says, “AI can now detect depression from your voice” and it is twice as accurate as a human practitioner. Interestingly, AI machines deliberate not based on the words spoken but on how you say it.
Kintsugi is a vivid example. The app can detect clinical depression and anxiety from 20-seconds of free speech. This app is currently integrated into call centers, telehealth platforms, and remote patient monitoring apps.
AI robots entertain elders and prevent depression. Robots, like Elique, are already the best companions of people who would otherwise feel lonely.
Artificial Intelligence Malpractice: Who is Responsible?
So far, we have illustrated all the benefits that AI and robotics can bring to humanity. But the coin has two sides. What if malpractice happens? Who is responsible for that?
Before we touch upon the liability issue, let’s contemplate the question of “what is the probability that AI machines will fail?” The good news is that the current studies predict a high level of accuracy for AI algorithms. For example, Pranav Rajpurkar et al. concluded in a study:
Deep learning algorithms can diagnose certain pathologies in chest radiographs at a level comparable to practicing radiologists on a single institution dataset.
After clinical validation, algorithms such as the one presented in this work could be used to increase access to rapid, high-quality chest radiograph interpretation.
That’s the good part of the story. But the argument goes on that we deal with machines rather than humans. If, in any case, malpractice happens, who is liable? The doctor who did not stop the machine? The manufacturer? The engineers who did not foresee a problem?
Right now there are no clear-cut answers to these questions. Zach Harned, Matthew P. Lungren & Pranav Rajpurkar believe that the unique capabilities of AI create an opportunity to argue that physician liability should be minimized.
Whether doctors that have little if any knowledge of how such complex algorithms are operated should be called to liability in case of AI malpractice is a matter of future legal regulations. The issue is even more complicated when the machines are developed to the level of taking independent decisions. As technology grows and these issues become acute, humans will find a more precise way of dealing with these problems.
We are already talking to Alexia and chatbots as a routine. So, AI and robots are there and they’re penetrating the medical field. Given all the benefits that data-driven algorithms can bring for the diagnosis, new drug development, treatment, and prevention of diseases, there are still open issues like the liability for malpractice.
We are yet to witness how the technology will evolve and how much power it will have over decision-making.
Are machines going to make independent decisions or will the humans be still in charge of the final act? This question is detrimental not only for the liability but for other risks involved in a tech-controlled world.