The healthcare industry is full of words and terms, often used interchangeably, but with subtle differences:
Recently another set of false synonyms is on the rise: healthcare artificial intelligence versus clinical artificial intelligence. The easiest way to differentiate between the two is to use the example of healthcare (macro) versus health care (micro) noted above.
Healthcare AI is an umbrella term that encompasses the many different forms of artificial intelligence used to support various health care functions. These could be administrative, financial, operational or clinical – from automated scheduling to virtual care assistants and supply chain management tools.
Clinical AI is the segment of healthcare AI that specifically focuses on AI technologies used to improve patient outcomes. It incorporates different types of artificial intelligence (i.e. machine learning, deep learning, natural language processing, computer vision) to help enable better, faster and more accurate diagnostic and treatment decisions.
While that’s a highly simplified definition of each AI use case, it’s worth noting there is still nuance and overlap between the two.
For instance, at Aidoc our focus is intelligent AI that can help individuals process large amounts of data, discover trends and accelerate decision making. This not only benefits clinicians and patients but also the health system at large with positive downstream implications on resources, revenue and costs. While our solutions can help reduce administrative burden (common examples of healthcare AI), it all stems from coordinated and efficient patient care (clinical AI).
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