Remember Big Hero 6's beloved Baymax? The lead character’s personal pudgy robotic healthcare companion was much loved and adored by the audience. We might not have wondered back then but the fascinating machine had actually been powered with Artificial Intelligence, programmed to scan a human body for any illnesses or injury while also examining the environment, offering treatment and even catering to the emotional requirements of the patient.
Although Baymax may appear as a complete fantasy creation from a children’s movie, yet technology and robotics engineers throughout the globe are now working on making healthcare AI become a practicality and reality from a fantasy.
At the initial stage, technology was merely used to automate the most routine and monotonous tasks and cut down on the use of paper through digitisation of health records while also aiding in the easy flow of this information among insurance companies, hospitals and patients. (Related blog: How is the Internet of Things (IoT) influencing the Human Body?)
While these tasks continue to be worked upon, Artificial Intelligence has expanded its applications from being restricted to enhancing back-office productivity, to emerge as an enabler to improve healthcare outcomes.
"By augmenting human performance, AI has the potential to markedly improve productivity, efficiency, workflow, accuracy and speed, both for [physicians] and for patients… What I’m most excited about is using the future to bring back the past: to restore the care in healthcare." - Eric Topol, MD, director and founder of Scripps Research Translational Institute quoted this in an interview with New York Times.
From hospital care to clinical research, drug development to insurance, AI applications are recasting the workings of the health sector to cut down on spending and enhance the outcomes of the patient. (Not only AI, but IoT also has application in Healthcare)
From employing it to detect links between genetic codes, put to use surgical robots or even for maximizing hospital efficiency, AI has proven to be boon for the healthcare industry
It's obviously imperative for the health professionals to take every crucial information into consideration while diagnosing patients. As a result, this leads to sifting through various complicated unstructured notes kept in medical records. If there's a mistake in keeping track of even a single relevant fact, the life of a patient could be put at risk.
The assistance of Natural Language Processing(NLP) makes it more convenient for doctors to narrow down all relevant information from patient reports.
(Now that I mentioned Natural Language Processing, to know more about this topic, you can also check out our other blogs on the subject)
Artificial Intelligence holds the ability to store and process large sets of data, which can provide knowledge databases and facilitate examination and recommendation individually for each patient, thus helping to enhance clinical decision support. (Various ML algorithms are deployed in order to decipher medical data, you may find similar application as “Bioinformatics”)
This technology can be relied upon by doctors for aid in detecting risk factors through unstructured notes. An interesting example of this is IBM’s Watson which examined the key indicators of congestive heart failure in almost 21 million patients over a span of six weeks, detecting the ones at risk of gaining the condition within a year in about 85% of the cases.
People have a tendency of booking appointments with their GP at the slightest threat or medical issue, which could often turn out to be a false alarm or something which could be cured of self-treatment.
Artificial Intelligence assists in enabling smooth flow and automation of primary care, allowing doctors to stress over more crucial and dire cases.
Saving money on avoidable trips to the doctor, patients can benefit from medical chatbots, which is an AI-powered service, incorporated with smart algorithms that provide patients with instant answers to all their health-related queries and concerns while also guiding them on how to deal with any potential problems.
These chatbots are 24/7 available and have the capacity to deal with multiple patients at the same time. (Learn the background of these chatbots that is incorporated with ML algorithms)
AI and collaborative robots have revolutionized surgeries in terms of their speed, and depth while making delicate incisions. Since robots don’t get tired, the issue of fatigue in the middle of lengthy and crucial procedures is eliminated.
AI machines are capable of employing data from past operations to develop new surgical methods. The preciseness of these machines reduces the possibilities of tremors or any unintended or accidental movements during the surgeries.
A few examples of Robots developed for surgeries are Vicarious Surgical which combines virtual reality with AI-enabled robots so surgeons can perform minimally invasive operations, Heartlander, a miniature mobile robot developed by the robotics department at Carnegie Mellon University, which was developed to facilitate therapy on the heart.
AI systems facilitate virtual nursing assistants that can perform a range of tasks from conversing with patients to directing them to the best and effective care unit. These virtual nurses are available 24/7 and can respond to queries as well as examine patients and provide instant solutions.
Presently many AI powered applications of virtual nursing assistants presently enable more regular interactions between patients and care providers between office visits to avoid any unnecessary hospital visits. The world’s first virtual nurse assistant Care Angel, can even facilitate wellness checks through voice and AI.
AI has the capacity to surpass human doctors and help them detect, predict and diagnose diseases more accurately and at a faster rate. Likewise, AI algorithms have proved to be not only accurate and precise at speciality-level diagnostics, but also cost-effective in terms of detecting diabetic retinopathy.
For instance, PathAI is developing machine learning technology to aid pathologists in making more accurate diagnoses. The company's current goals include reducing error in cancer diagnosis and developing methods for individualized medical treatment. (Other than medical and healthcare applications, Machine Learning also has these 7 applications in daily life)
Buoy Health is an AI-based symptom and cure checker that uses algorithms to diagnose and treat illness. Here's how it works: a chatbot listens to a patient’s symptoms and health concerns, then guides that patient to the correct care based on its diagnosis.
(You can also take a look at our blog on How is AI being used in the fight against COVID19?)
As per a report from the Brookings Institution, there are several risks associated with AI in healthcare that need to be addressed. Below are a couple of the threats which had been identified by the Institution’s report :
One of the biggest risks that AI in healthcare holds is that the AI system might at times be wrong, for instance, if it suggests a wrong drug to a patient or makes an error in locating a tumour in a radiology scan, which could result in the patient’s injury or dire health-related consequences.
AI errors are potentially different for at least two reasons. While errors can obviously take place by human medical professionals as well yet what makes this crucial is that an underlying error, error in an AI system could lead to injuries for thousands of patients.
Yet another threat posed by AI systems is that training these systems requires massive amounts of data from multiple sources which include pharmacy records, electronic health records, insurance claims records etc.
Since the data is fragmented and patients often see different providers or switch insurance companies the data gets complicated and less comprehensible as a result of which the risk of error and the cost of data collection escalates.
(Moulding massive amounts of data into crucial information, learn the 5 decisive steps for Qualitative data analytics).
Threats of Artificial Intelligence in Healthcare
Collection of huge datasets and exchange of data between health systems and AI developers to enable AI systems leads to many patients believing that this could violate their privacy, leading to the filing of lawsuits.
Another area where employment of AI systems raises this issue is that AI has the capability of predicting private information about patients even if the patient has never given the information.
For instance, Parkinson’s disease could be detected by an AI system with the trembling on a computer mouse even if the person hasn’t revealed the information to anyone else which could be considered a violation of privacy by the patient.
Since AI systems absorb and learn through the data with which they are trained, they can also absorb the biases of the available data. For example, if the data incorporated in AI is mainly collected in academic medical centres, the developing AI systems will have less awareness about, and as a result, will treat less effectively, patients from populations that do not typically frequent academic medical centres. (Related blog: Do Blockchain and Artificial Intelligence Incorporate an Ideal Model?)
In the long run, the employment of AI systems could lead to shifts in the medical profession. Particularly in areas like radiology where most of the work gets automated.
This raises the concern that high degree of employment of AI might lead to a fall in human knowledge and capacity over the years, making providers fail in detecting AI errors as well as in the further development of medical knowledge. (As it is a threat, or possibly a misconception, real similar myths about Artificial Intelligence)
While this technology still looms over certain layers of dangers and perils, Artificial Intelligence tools can aid the medical industry in enabling faster service, more accurate diagnosis and analysis of data for detecting trends or any genetic information that would expose someone to a particular disease.
We exist in an era where saving even a couple of minutes can save lives and in these times, Artificial Intelligence and machine learning can be transformative not only for healthcare but for every single patient.
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That was quite an informative article, thank you for sharing it with us! I do believe that AI has a lot to offer when it comes to the healthcare industry. I am sure you'd find this of interest just as I did, here’s globally-renowned Cloud influencer, Kevin Jackson on the impact of AI on HealthTech and EdTech https://www.engati.com/blog/kevin-jackson-ai-healthtech-edtech . You should look it up, it's quite insightful!
Thank you! Will take a look!
Amazing article, i know a few companies who are into using AI to help radiologists and doctors in faster diagnosis. Do check them out https://idoc.ai/ (iDoc.ai) and https://oliveai.com/ (Olive AI). As a medical researcher I was extremely interested in these companies.
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Whether it’s about the cost management, new medical research for diseases like cancer, time optimisation, with minimal errors & mistakes, AI and the Internet of Medical Things (IoMT) is already helping people in a great extent in the healthcare sector and will continue to do even more in the near future.