The Effects of Artificial Intelligence on The Healthcare Field

Artificial intelligence is expected to revolutionize the medical industry in the near future. Venture capitalists are currently seeing the field as a realistic way to disrupt the economy and make extraordinarily large leaps in progress towards better treatment for patients. AI startups are no longer seen as risky, long-shot investments. Rather, they’re being treated as a necessary step towards effective and cost-efficient business practices. Radiology is currently one of the more impacted fields in medicine, as researchers in artificial intelligence have been able to use statistical analysis tools and massive data collections to speed up the existing workflow. The field currently suffers because there are usually extremely long wait times for patients. This generally results in worse health outcomes. However, these wait times can be drastically shortened with advancements in certain identification techniques aided by artificial intelligence. Massive consumer savings are a very likely result of this technology being adopted.

Certain interest groups are currently looking to fund research into artificial intelligence solutions to identifying pneumonia. Due to the frequency of the incidence of pneumonia, identification techniques aided by artificial intelligence have a very real potential to decrease costs and save human lives. In 2018, a movement was lead by Kaggle, which sponsored a $30,000 reward for the more effective artificial intelligence solutions to the pneumonia identification problem. Amazon Web Services are also advocating for the development of artificial intelligence solutions to medical issues. As of 2018, the company released a HIPAA compliant tool that is able to glean relevant information from unstructured medical texts and retrieve medical diagnoses and treatments. An important feature of their tool is its ability to protect patient information. Though the data needs to be accessed at least once by the machine in order for it to work, the service is able to protect patient confidentiality.

Artificial intelligence is also being used to identify and save patients of sepsis. The condition can be cured with a few readily-available drugs, but it’s not always apparent when the condition is present. This frequently leads to death because the condition develops quickly and is not easily noticeable. According to medical professionals, the condition can often be mistaken for exhaustion or dehydration. These are nearly always benign conditions that can be cured with rest and fluids. Unfortunately, patients with sepsis can see their health decline very quickly, and they often need urgent medical treatment before their symptoms begin to noticeably worsen.

The year 2018 was a particularly AI-focused year for the Radiological Society of North America. Interestingly, some medical professionals say that artificial intelligence algorithms are frequently unable to properly identify underlying medical conditions when they are used with different sorts of medical equipment. For example, a radiological tool manufactured by Fuji will perform nearly identically to a tool manufactured by Siemens, but the artificial intelligence algorithm that is trained on Fuji equipment will not necessarily be able to perform at the same level when applied to Siemens equipment. This problem is currently the focus of some medical researchers. Ultimately, the best medical outcomes are going to be achieved through a combination of artificial intelligence and human supervision.

Some individuals would question the place of artificial intelligence within the medical field and draw comparisons between artificial intelligence solutions and clinical decision support tools. For an example, clinical decision support tools include devices such as heart-rate monitors that alert practitioners when the rate crosses a certain threshold. As certain authors point out, the effectiveness of clinical decision support tools varies, and the medical field goes through “regular cycles of hype and disillusionment.” This is not to say that clinical decision support tools have had a negligible effect on medicine. The reality is in fact the opposite. These tools are regularly used to save lives, and the medical field would be much worse off without their aid. Ultimately, artificial intelligence solutions outperform most traditional clinical decision support devices due to their ability to predict outcomes for the patient if treatment is administered. To further draw this distinction, heart-rate monitors are unable to give a diagnosis or recommend that treatment be administered. Artificial intelligence algorithms are able to do this. The impending issue with technological intervention is not immediately apparent. Through the increasing automation attained with technological advancements, the future of medicine may actually look rather unsettling. Our current reality is one with an unbelievable amount of information that needs to be interpreted by trained doctors. This amount of information is always going to be increasing, and it is likely going to increase exponentially as technology is made cheaper and more readily available. At a certain point, it will be unrealistic to expect an individual to operate efficiently with all the available information, and patients will be unable to get a diagnosis within the proper amount of time. In my opinion, the alternative to this is almost equally depressing. If doctors are unable to do the majority of diagnosing themselves, the only other option we have is to replace doctors with automated medical agents that recommend tests and treatment in place of a human doctor.

Though the personal element to medicine may be diminishing in the future due to these advancements, the future of this technology is not all dim. Through cost-saving methods and broader international movements, artificial intelligence will likely make access to high-quality medicine more available all across the globe. Currently, areas like China and West Africa are facing severe shortages of trained medical professionals, and are unable to properly serve the demands of low-income areas. Previously, x-ray results needed to be reviewed by a medical professional to identify conditions like tuberculosis. With the advent of AI, this process can be significantly sped up. In certain instances, a diagnosis made by a computer can be as accurate or more accurate than a diagnosis made by a human agent. The benefits of this are quite profound because an AI can save time, money, and lives. Still, an unfortunate and likely overlooked side-effect of this technology being adopted is that the medical algorithms are usually trained on subjects that are from a different region. If the relevant medical data is only relevant to individuals from other parts of the world, the effectiveness of these robotic doctors will be severely diminished. This only means that doctors will likely need to verify that the results they achieve are applicable to individuals everywhere.

Perhaps the most useful function of AI is its ability to consume and interpret massive amounts of data in an incredibly short period of time. Our current medical system is burdened with enormous amounts of patient health records that could never be thoroughly examined by human beings. Furthermore, these records need to be interpreted by an individual in order to be useful. This presents a challenge for researchers, but this problem will be significantly mitigated in the near future. Once the data is properly formatted and digitized, computer analysis will be able to make predictions that humans likely won’t be able to match. There are certain medical conditions that exist regionally that likely have an extremely subtle influencing factor. These influencing factors are often difficult to pin down for human agents, but computerized statistical analysis methods are likely to simplify this process and make diagnoses faster and more accurate than ever before. Furthermore, due to the incredible data-crunching capacity of AI, data from smartphones and other more available medical monitoring tools can be harnessed to improve the quality of computerized diagnoses. Nearly everybody owns a smartphone, but the mere capacity for smartphones to harvest data alone does not improve medicine. Only through computerized medical tools can they be used to improve the health outcomes for the general population.

The future of Artificial intelligence within the medical world is very bright. Radiology is likely to begin to see the impact first as there are already high-functioning tools in use that are improving the health outcomes for patients of tuberculosis and pneumonia. Through a combination of artificial intelligence and human intervention, affordable and high-quality healthcare will become more and more available for people all over the world. Even when these tools aren’t being used to directly make diagnoses, they will certainly be effective at improving the efficiency of doctors. Through reducing their workload and increasing their efficiency, these highly skilled individuals, which are in short supply, will be able to serve their communities in a way that they have never been able to before using AI assistance.