AI: Cutting Edge Technology Entering Healthcare?

The healthcare sector is one of the most important markets in the United States economy. The implementation of the modern healthcare system has allowed the overall quality of life in the United States to drastically improve since the last century. For instance, the infant mortality rate has declined from 12.6 deaths per 1,000 live births down to 5.9 over the span of 1980-2016 [1]. Such strides in America’s aggregate quality of life would not have been possible without the implementation of healthcare systems. However, these systems’ hidden flaws, inefficiencies, and inequities continue to propagate yearly health concerns such as the flu, necessitating additional solutions for greater societal benefit. Alongside growing inequities are strides in innovation: a recent proliferation into research and development of artificial intelligence (AI) has spilled over into healthcare. For instance, it is projected that the healthcare-centric AI industry will grow around 42% per year into 2025 [2]. It is evident that change is coming. What is catalyzing this interest in healthcare AI? What are examples of ventures and endeavors aiming to improve healthcare through this nebulous new innovation? And most importantly, how will these endeavors have built upon these innovations impact healthcare?

One area of the United States healthcare industry with concern for inefficiency on a large scale is in clinical laboratory testing, valued at $176.7 billion [3]. An example of the industry’s sheer costs and profits of the industry can be analyzed by examining the projected 700 million predicted to be living with diabetes, and thus testing for and monitoring diabetes. Like diabetes, other chronic diseases affecting large numbers of individuals are also creating an astronomical demand on clinics, laboratories, and healthcare systems. Such demand, as concluded previously, will inevitably lead to inefficiencies and therefore misdiagnoses. According to the University of California, San Francisco, misdiagnosing illness and medical errors account for approximately 10% of all US deaths [2].

Fortunately, this harrowing statistic has not gone unnoticed by medical professionals and innovators in healthcare. New ventures, such as Buoy Health – a startup leveraging AI to help patients determine diagnoses and next steps for treatment – have utilized AI to improve diagnostic test distribution and analysis, lowering the margin of error to a far lower frequency [5]. By using algorithms & national databases and combining them with AI, Buoy has been able to develop an individualized AI chatbot. Through a series of questions, the chatbot is able to guide the user to the most probable prognosis, as well as guide the user to specialists. Innovations in diagnostic testing such as Buoy could prove extremely useful towards enforcing equal access to quality testing and lowering the rate of dangerous misdiagnoses.

It is already clear that AI is proving useful in the healthcare market; for example, new innovations in AI have also helped make essential strides in deciphering recent public health events, such as the COVID-19 pandemic. Recently, AI was implemented to analyze the composition and compatibility of one billion small molecules to determine their ability to bind to SARS-CoV-2 proteins [6]. It was discovered that particular drugs such as Baricitinib can weaken SARS-CoV-2 and its proteins, making it more manageable by the human immune system. Baricitinib is a Janus kinase inhibitor, which can bind to receptors on immune cells, blocking the receptor pathway to make more cytokines that cause immune system reactions. This leads to the body’s reaction from COVID-19 being milder, meaning a smaller chance lungs and components of the airway are affected and lowering the chance of intubation. The knowledge from this discovery was quickly implemented in hospitals across the country, leading to a contribution towards the effort to reduce the spread and severity of COVID-19. More importantly, such a discovery would not have been possible simply by human means or through present computer models. By utilizing the hyper-efficient recursive algorithms that comprise the AI model, billions of molecules could be analyzed in days when it would normally take years to be analyzed through other methods.

Whether employed on diagnostic testing or discovering biochemical breakthroughs, AI has a place in healthcare. Its ability to execute at a higher level than humans for a longer period of time with fewer inherent biases makes it an invaluable asset. Ambitious initiatives such as contact tracing, symptom tracking and diagnosis, hospital organization, and more can now be handled with relative ease by both healthcare professionals and everyday citizens. •