In years past, it seemed that much of the medicinal world in modern society was beyond advanced - we were well past understanding much of the common ailments. After the grandiose hit of the Covid-19 pandemic, however, a rude awakening was bestowed upon humanity. Many countries have been put in dire circumstances that would have never been imagined by the minds of citizens that resided prior to the enormous backlash that the virus caused.

As the cure to this wretched disease continues to be sought, there is a great lack of organization in emergency care facilities that could be amended. Even then, there is still work that must be done to ensure safety on a day-to-day basis as many people continue to learn of the importance in wearing a mask. In the midst of a pandemic that has (arguably) successfully torn apart the world, how can the medicinal industry as a whole find a way to persist in their efforts to seek hope?

The answer (of all places) lies not in humanity itself, but in innovation - specifically, in artificial intelligence. Though many imagine terrifying cyborgs in a quest to overtake the Earth, artificial intelligence is actually a largely growing and imperative subject in the modern world. With AI imported as a widely-used utility in the medicinal fields of practice, it will: provide more accurate skill in application of procedural practices, help limit long-term costs of industry labor, and reduce risk factors that both operators and patients face.

What is Artificial Intelligence? Before moving on to how artificial intelligence can assist in the medicinal industry, it is important to understand just what artificial intelligence is. Though it is highly publicized in much of modern media, very few truly understand the correct denotation of the term. According to multiple opinion surveys, even top commercial leaders are without possession of an in-depth comprehension of the subject, and most average people associate it too often with the man- destroying robots drawn up in fictional realms (West). Generally, artificial intelligence refers to a “digital computer or computer-controlled robot” having the capability to complete tasks that require the knowledge possessed by intellectual beings (“Artificial Intelligence”).
However, due to the numerous meanings of the term to numerous different people, AI has been the topic of much debate. Because it is a subject that is not well-known, it is considerably frightening for humans to delve in. For example, Alan Turing is normally attributed to the first utilizations of the term, creating the “Turing Test” (a simulation in which a person attempts to understand whether they are interacting with a human or an AI machine) which indicates that computers should complete logical tests at the same level of humans before being deemed as “thinking” autonomously (West; “Artificial Intelligence: The Turing Test”).

A few years later, however, John McCarthy used the phrase “artificial intelligence” in “getting a computer to do things which, when done by people, are said to involve intelligence” (West). Due to the lack of definite answers and the ever-present variability in the realm of AI, it can (understandably) seem somewhat of a risk to involve it in the area of life that solely deals with human health. However, when moving away from the emotional points of focus and into those regarding the logical statistics of artificial intelligence, its great benefit to the human race is easily made transparent.

Application Precision

Quality of care for the patient is a large factor in determining AI”s use in the medical field. For example, though artificial intelligence may never be able to fully replace a physician, they can definitely become great tools to be implemented as guides for when humans make simple mistakes. For example, investigators at Seoul National University Hospital and College of Medicine created in 2018 an artificial intelligence algorithm known as deep learning-based automatic detection (DLAD); designed to scrutinize chest radiographs for unnatural cell growths (possible cancers), DLAD performed better than seventeen out of eighteen physicians on the same images (Greenfield). This figure represents a machine that outperformed approximately ninety-four percent of highly-qualified professionals who deal with these matters in their daily lives.

Another example of AI’s accuracy in medicine is demonstrated by those researching at Google AI Healthcare. In 2018, they were able to establish an artificial intelligence algorithm “LYNA (Lymph Node Assistant)” that examined histology slides to find “metastatic breast cancer tumors from lymph node biopsies” (Greenfield). Though LYNA was not the first attempt at using artificial intelligence in order to study histology slides, it was able to find areas of interest that were unnoticeable to the naked human eye with given biopsy samples; tested on two data sets, LYNA was able to precisely categorize a sample cluster as cancerous or noncancerous ninety-nine percent of the time (Greenfield). Moreover, when LYNA was provided to physicians to be used along with their normal slide analysis method, “LYNA halved the average slide review time” (Greenfield).

Applications such as DLAD and LYNA can be used by physicians in brevity to provide a check for their initial work and decrease the time needed for patient data analysis while maintaining accurate results; at length, these algorithms and algorithms of the like could operate independent of physician use, permitting “doctors to focus on cases that computers cannot solve” (Greenfield). Both of these applications provide prime examples of how incredibly great the precision technology can yield in comparison to man, as well as their improved efficiency when viewed side-by-side to that of their creator.

Limiting Costs of Industry

A great aspect of importance when considering artificial intelligence in medicine is the cost of resources. The Organisation for Economic Co-operation and Development (OECD) predicts that twenty percent of “healthcare spend is wasted globally,” while the United States Institute of Medicine believes this figure to be closer to thirty percent (Bernaert). One largely upsetting reason for this misuse of funds is a result of the fact that there are amendable inefficiencies of the system that could be reduced with the employment of AI.

It is no secret that being able to communicate and document information creates a greater advantage for effectiveness to ensue - and the field of medicine is no exception. Whilst doctors move toward interchangeable standards for tracking patient data, AI systems can be more easily implemented in order to identify the best treatments for patients’ throughout multiple clinics due to the similarity of data input (Bernaert). This in turn creates customized approaches to each patient with regard to their pre-existing medical history and patient profile in order to help doctors within multiple practices receive suggestions on the best treatment for the patient. This will provide great relief in commerce by reducing costs related to complications after treatment, “one of the key drivers of cost in most healthcare ecosystems across the world” (Bernaert).

Moreover, as demonstrated above, artificial intelligence algorithms can help alleviate not only a lack of accuracy, but also a surplus of time. When considering notions such as the effect of osteoporosis on commerce - a condition that takes about “£1.5 billion annually” from the United Kingdom’s National Health Service - the earlier diagnosis and treatment of illnesses such as these (which are often missed by the human eye) can help reduce the need for the large investment this disease forces the health service to make by preventing the illness from occurring (Bernaert). Furthermore, artificial intelligence has the capability to develop drugs at a faster rate, which could save innumerable costs that could then be utilized elsewhere.
For example, the University of Toronto promoted a start-up that was able to program a computer to simulate the analyses of “millions of potential medicines” to forecast their efficiency against Ebola, effectively saving expensive tests and - most crucially - lives “by repurposing existing drugs” (Bernaert).

By the methods exhibited above, there is definitely evidence to support the value that AI has on the commercial aspects of the healthcare industry. Risk Reduction Though there are numerous pillars of support to encourage AI in the medical field for the sake of the patient, there are also reasons to do so in mind of the healthcare workers as well. Primarily, there is a risk reduction in patient contact. When performing procedures that require interaction between the provider and patient, though many precautions may be thoroughly taken and well-planned, there is no way to provide a one hundred percent guarantee for the doctor’s safety as well; if the physician of a clinic is infected by one patient alone during an encounter, then the remainder of clients of that same doctor will either: encounter the disease themselves in the time during the doctor is unbeknownst to their illness, or will not be given the medical treatment they require due to a lack of a provider after the physician does know of the issue (McCue).

With artificial intelligence performing the actual interactions in place of humans, this risk of creating spread can finally be wholly eliminated.


Though AI represents a field of much undiscovered terrain, that which we know of it now could provide useful technology in creating a medical industry of optimal stature. If these three benefits stated above are plausible alone from the lack of artificial intelligence in medicine, imagine what we could actually experiment with and hypothesize as further benefits after artificial intelligence is implored on a larger scale. There is still much to learn, however this is just the beginning of a process that will ultimately lead the world to a practice of medicine that is much more efficient than it once was. Especially considering the circumstances of the world at this moment with the pandemic producing a grand abundance of much-needed caution, there seems to be a greater want than ever for AI in healthcare fields.

To humanity’s credit, though, it is hard to trust something that is not human. This arrogance, however, in man’s skill might have been a contributing factor as to why the state of the world is as intense as it is at this moment. Had artificial intelligence been promoted more promptly and more greatly, who knows what innovations could have already been established in order to help the world? Strictly speaking, there is one great benefit and one great downside to having an all-human, no-AI medical industry: only humans are in charge, but only humans are in charge.

Author's Bio: 

I am a computer science professor. Being a tech enthusiast I keep close tabs on trends and will be glad to share and discuss the latest wrapups in the field with the community.