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The pluses and minuses of AI in healthcare

It is expected that, in 2022, artificial intelligence (AI) and machine learning will continue to impact healthcare in a multitude of ways, not the least of which are predictive modeling, diagnoses, patient experience, and drug discovery. Indeed, this is a promising turn of events, given the aging U.S. population and the dearth of doctors that is expected in the years ahead.

With about 10,000 Baby Boomers turning 65 every day, there are expected to be 95 million in the U.S. by 2060, nearly twice as many as in 2018. That will result in enormous strains on the healthcare system, especially given the fact that eight of every 10 American seniors suffer from at least one chronic condition and nearly seven in 10 suffer from two or more.

Couple that with the fact that there is expected to be a shortage of as many as 104,900 doctors by 2030 and it’s easy to see that the need for time-saving (and ultimately life-saving) technology is only going to rise.

If there has been any good news to come out of the pandemic, it is that healthcare organizations have been forced to confront the emerging reality more quickly than they might have otherwise. According to the Accenture Digital Health Technology Vision 2021 report, 81% of the healthcare leaders believe their organization’s digital transformation has been accelerated and 93% had made it a priority for 2021.ADVERTISEMENT

All indications are that that’s going to continue, and that AI will be a particular focal point. The AI healthcare market is expected to rise in value to $39.5 billion by 2026, over six times more than it is currently.ADVERTISING

While some have sounded cautionary notes about AI in this sector—concerns we will cover later in this piece—here are the areas in which AI is making its presence felt:


Because AI can use the information provided by genome sequencing to project which compounds might work against a given target, European pharmaceutical companies, like the UK-based firm Exscientia, have been able to use the technology in an attempt to develop a Covid-19 vaccine. That led to Exscientia entering into a one-year agreement in September 2021 with the Bill and Melinda Gates Foundation to develop medication that is more accessible to patients and less susceptible to variants.

That same month, researchers at Baylor College of Medicine and India’s Amity University announced that they had developed an AI platform that can target not only Covid-19 but Chagas disease, an infectious ailment common in South America that results in damage to the heart and central nervous system.


AI is capable of analyzing data from various sources—electronic health records, images, therapies, etc.—and developing models that will predict the best possible approach to any given patient’s care journey, thereby streamlining operations and ensuring the most favorable outcomes.

IBM researchers, for example, have partnered with scientists from two healthcare systems to use AI to examine EHRs for clues about the warning signs of heart failure, which has long been the leading cause of death in the U.S. As a result, the team was able to develop a model that predicted this malady as much as two years earlier than previous methods.


This might be the most dramatic example of all, as AI applications have been developed that simplify EHR data entry/retrieval and enhance telemedicine, which has risen to prominence during the pandemic.

In October 2021, Amazon announced plans to install Alexa technology at various healthcare facilities throughout the U.S., enabling patients to remain connected not only with healthcare professionals but also their loved ones. (This calls to mind the PadInMotion technology we use at The Allure Group, a network of six New York City-based skilled nursing facilities, which, while not AI-based, accomplishes the same task.)

In addition, there is the expectation that, in 2022, 45% of all operating rooms will feature AI integration, making more efficient operations possible through the use of robotic surgery and the like.

Not to be forgotten, either, is the manner in which wearables and wellness apps enable users to track such things as heart rate and oxygen level while also alerting others to falls. Still in development is something called acoustic epidemiology, a form of AI that can determine the severity of a patient’s illness simply by hearing a person cough into a smartphone.

As noted, there are those who point out that AI, while obviously promising, still has its shortcomings in the healthcare sector. In an article on Innovation Origins, tech expert Jarno Duursma said there are many things he likes about the technology but noted that software does not necessarily provide all the answers. He cited AI that analyzes images of moles and makes a determination about whether it might be able to detect a malignancy or not as an example. Other experts cite privacy and security concerns.

Still, the upside of AI in this sector appears to be limitless and much-needed, given the short- and long-term challenges facing those working within it.

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