Artificial Intelligence in Healthcare: Applications and Threats

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. 

 

In line with this, over the years, the power of technology particularly AI has escalated by leaps and bounds in various industries like AI in education, Sports such as AI in football, AI in manufacturing, as well as AI in the healthcare industry. 

 

AI in Healthcare

 

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 digitization of health records while also aiding in the easy flow of this information among insurance companies, hospitals, and patients.

 

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. Particularly in the present scenario of the COVID era. While taking a toll on the personal health of the people, COVID has played a huge part in putting the developing AI technologies into practice. The technology has paved its way to developing new models, exploring new treatments, as well as in developing the vaccine.

 

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.

 

Also Read | Big Data in healthcare industry

 

Applications of AI 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 a boon for the healthcare industry

 

1. Support in Clinical Decisions

 

It's obviously imperative for health professionals to take every crucial piece of 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. 

 

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.

 

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 has been employing AI for predicting heart failure. 

 

Also Read | Bioinformatics

 

2. Enhance Primary Care and Triage through Chatbots

 

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.

 

3. Robotic Surgeries

 

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 possibility of tremors or any unintended or accidental movements during the surgeries. 

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Robotic Surgery

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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 as well as Heartlander, a miniature mobile robot developed by the robotics department at Carnegie Mellon University, which was developed to facilitate therapy on the heart. 

 

4. Virtual nursing assistants

 

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.

 

5. Aiding in the accurate diagnosis

 

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 specialty-level diagnostics, but also cost-effective in terms of detecting diabetic retinopathy. 

 

Also Read | Machine Learning tutorial

 

6. Minimizing the burden of EHR use

 

EHRs have played an integral role in the healthcare industry’s journey towards digitalization, yet its switch has introduced a variety of issues in association with cognitive overload, endless documentation, and user burnout.

 

The EHR developers have started making use of AI for creating more intuitive interfaces and automating a couple of the routine processes that consume a great degree of the user’s time.

 

While voice recognition and dictation are helping in enhancing the clinical documentation process, yet natural language processing (NLP) tools may not go as far. AI can also aid in processing routine requests from the inbox, such as medication refills, and result in notifications. It can also aid in prioritizing tasks that require the clinician’s attention, making it simpler for the users to operate with their to-do lists.

 

What are the Threats of Artificial Intelligence in Healthcare?

 

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 :

 

1. Errors and Injuries

 

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 tumor 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, an error in an AI system could lead to injuries for thousands of patients.

 

2. Data availability

 

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.

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Threats of AI in Healthcare

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3. Privacy concerns

 

The collection of huge datasets and the 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 the 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.

 

Also Read | AI in the law industry

 

4. Bias and inequality

 

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 centers, 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 centers. 

 

5. Could lead to shifts in the profession

 

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 a 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.

 

Also Read | Myths on Artificial Intelligence

 

Conclusion

 

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 data analytics 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.