How AI Is Shaping Healthcare and Pharmaceuticals

In healthcare and pharmaceuticals, Artificial Intelligence (AI) is driving transformative changes that are enhancing personal medical care, and these are the latest game-changing developments in the industry.
The gradsingapore Team
Brendan Yee
How AI Is Shaping Healthcare and Pharmaceuticals

When it comes to reaping the benefits of AI, one of the sectors that stands to gain the most is the field of healthcare. A constant hotbed of creative exploration, the use of such systems can lead to improvement in patient results by 30% to 40%, and lower the cost of care by 50%, according to Frost and Sullivan.

Aside from patient care, the use of AI platforms helps to resolve issues like manpower shortages, while also enhancing the overall efficiency of medical services. More critically, they are able to increase accuracy before, during, and after the treatment, which is vital to diagnosis and administering lifesaving care.

With such valuable advantages, it's unsurprising that these models have been gradually integrated into the existing healthcare framework. It would also be helpful for those eyeing a career in this sector, so they’d know what to expect upon getting their first job.

Virtual assistance program

Manpower is often a pressing issue in the healthcare industry, particularly in countries like Singapore. This is concerning, considering that one-fifth of the population is aged 65 and above, and there is a need for existing care facilities to expand their capacities to accommodate this shift in population.

However, not only would manpower troubles be rectified with the introduction of AI, but it can also spawn an entirely new way of managing and assisting patients. Tools like chatbots and virtual assistant apps designed specifically to reduce wait times for treatment and discharge by being available 24/7 and providing basic support.

AI Healthcare_01

An example of such a system is Selena+, that is currently employed across all polyclinics in Singapore. This platform uses machine learning models to examine pictures of a diabetic patient’s retina, and is capable of detecting diabetic damage with a precision rate of over 95 to 97%. This helps to reduce the amount of time needed to inspect every retinal photo manually, increase the overall efficiency of the care delivery and streamline the need for more manpower.

Aside from that, such systems also allow users to do everything from scheduling their own appointments, to collecting their prescription medication and reviewing test results. This empowers patients to manage some aspects of their own care, and facilitate collaboration between the patient and professionals for a more comprehensive experience.

This is essential as the healthcare sector also operates as a service, with 83% of patients indicating that inadequate communication leads to an unfavourable experience. As such, using models like natural language processing and predictive models can greatly reduce the chances of such incidents occurring. Accurate information can be delivered directly to both care provider and receiver, which fosters a better chance of meaningful and effective dialogue, and brings about the best forms of care for patients.

Reduction of human error

The nature of this sector is intense, especially when medical emergencies can crop up at any time. As a result, this frantic, fast-paced environment can often be the perfect breeding ground for human error, which is highly detrimental in this sector.

Administration and dispensing of medication is an instance of a task that requires a high level of meticulousness and proficiency, where even the smallest slip-up can negatively impact patients. However, with the adaptability of smart systems, medical staff will not only be able to better diagnose patients, but also make more informed decisions about how to treat them, among other functions.

AI Healthcare_02
Credit: John Hopkins Medicine

A good example is IBM’s clinical decision support system Merative, which collates and analyses patient medical information to provide treatment recommendations based on evidence, identify possible drug interactions or allergic reactions, and cut down on medication errors.

This includes identifying the outcomes of possible drug interactions and in turn, avoiding the risk of potential toxicity within a patient that could arise from using certain combos of medication in a single setting.

Innovation in medical procedures

Another area in which AI can further enhance healthcare is within medical procedures like surgeries. By integrating cutting edge AI technology alongside robotics, this could help further improve their efficiency by reducing the risk of complications during it.

Such examples include working with sensitive organs and tissues to help reduce blood loss and potential infection. This is done with tools like the Senhance Surgical System, that allows the surgeon to operate robotic arms that are equipped with reusable tools remotely. The procedure is viewed through a state-of-the-art 3D HD system that aids in precision and improved dexterity of the entire platform.

AI Healthcare_03
Credit: Karger Research

Systems with machine learning capabilities can also develop the ability to anticipate possible errors. According to the American College of Surgeons, they are currently using a platform that can project the course of a procedure 15 to 30 seconds before it occurs by analysing surgical videos and creating a predictive model based on the information.

Experienced surgeons can therefore be assured that even with years of medical training and hands-on work under their belts, they have a safety blanket of sorts to fall back on to ensure everything goes smoothly. For newer medical experts, they can make use of this resource as part of their training, like learning how to tie a suture across a wound as demonstrated by a machine created by the University of California.

The influence of AI on healthcare and pharmaceuticals

Given that the healthcare infrastructure in Singapore has already begun adopting AI systems in places, like using a predictive model called PAC+ in emergency rooms, the country is continuing its push to integrate smart systems into every level of medicine with the development of new, specific platforms.

This not only reduces critical aspects like cost, but also bolsters the public’s faith in the medical sector while increasing the success rate of treatments and saving many lives in the process. It is therefore essential for prospective healthcare professionals to upkeep their skills and knowledge about such advancements to maintain their competitive edge. This allows them to facilitate their entry into the healthcare workforce and enhance their marketability as potential hires as they make their first foray into the workforce.