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Much has been said about the potential of artificial intelligence to cut costs and better patient outcomes in healthcare. The technology has wide-reaching applications, including streamlining administrative functions like scheduling and billing, matching patients with physicians and even acting as a standalone diagnostic agent. As the coronavirus surged in the U.S., AI became a key tool in the public health response, from assessing people’s symptoms online to resource allocation. Some wearables manufacturers are even seeing if an algorithm, in tandem with their devices, can flag COVID-19 cases prior to becoming symptomatic. However, AI has its drawbacks, and plenty of detractors. AI as a diagnostic is still proving its efficacy, and can only be applied to very specific diseases that present in a rote manner. Industry also needs to solve AI’s "black box" problem, ensuring doctors and administrators are aware of how an algorithm arrived at a clinical recommendation without blind reliance on the technology. And developers need to ensure they’re training their algorithms on an inclusive and diverse dataset to avoid bringing existing human bias into the realm of the machine. But amid mounting investor interest in the space, it’s clear AI applications in healthcare will only continue to grow and could accelerate as COVID-19 hastens health tech adoption. |
