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Artificial intelligence and health care both deal heavily with issues of complexity, efficacy, and societal impact. All of that is multiplied when the two intersect. As health care providers and vendors work to use AI and data to improve patient care, health outcomes, medical research, and more, they face what are now standard AI challenges. Data is difficult and messy. Machine learning models struggle with bias and accuracy. And ethical challenges abound. But there’s a heightened need to solve these problems when they’re couched within the daily life-and-death context of health care.
Then, in the midst of the AI’s growth in health care, the pandemic hit, challenging old ways of doing things and pushing systems to their breaking points. In our upcoming special issue, “AI and the future of health care,” we examine how providers and vendors are tackling the challenges of this extraordinary time.
The biggest hurdle has to do with data. Health care produces massive amounts of data, from electronic health records (EHR) to imaging to information on hospital bed capacity. There’s enormous promise in using that data to create AI models that can improve care and even help cure diseases, but there are barriers to that progress. Privacy concerns top the list, but worldwide health care data also needs standardization. There are still too many errors in this data, and the medical community must address persisting biases before they become even more entrenched.
When humans rely on AI to help them make clinical decisions like injury or disease diagnoses, they also have to be aware of their own biases. Because bias exists in the data AI models are built upon, practitioners have to be careful not to fall into the trap of automation bias, relying too much on model output to make decisions. It’s a delicate balance with profound impacts on human health and life.
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The pandemic has also challenged the practical day-to-day functions of health care systems. As COVID-19 cases threaten to overwhelm hospitals and patients and doctors risk infection during in-person visits, providers are figuring out how to deliver patient care remotely. With more doctors shifting to telemedicine, chatbots and other tools are helping relieve some of the burden and allowing patients to access care from the safety of their own homes.
For particularly vulnerable populations, like senior citizens, remote care may be necessary, especially if they’re in locked-down residential facilities or can’t easily get to their doctor. The technologies involved in monitoring such patients include wearables that track vitals and even special wireless tech that offers no-touch, personalized biometric tracking.
These are sea changes in health care, and because of the pandemic, they’re coming faster than anyone expected. But a certain optimism persists — a sense that despite unprecedented challenges to the medical field, careful and responsible use of AI can enable permanent, positive changes in the health care system. The astonishing speed with which researchers developed a working COVID-19 vaccine offers ample evidence of the way necessity spurs medical innovation. The best of the technologies, tools, and techniques that health care providers are employing now could soon become standard and lead to more democratized, less expensive, and overall better health care.
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