Cognition is the ability to acknowledge patterns in data and consider what they might actually mean — much like the diagnostic approach of any good clinician. However, in the field of AI, many developers have become fixated on machine learning, which focuses heavily on imitating human intelligence, with a complete absence of cognition and is essentially attempting to view the human body as an algorithm. We all know the human body is far more complex than a simple algorithm and a digital solution capable of solving the current healthcare crisis must be able to understand that each individual is unique, as is their lifestyle, medical history and family history.
Once you are able to combine those factors and produce actionable medical advice through the analysis of vital sign data, then you could limit the amount of chronic diseases and unnecessary trips to the doctor. Benjamin Franklin (1736) once said that “An ounce of prevention is worth a pound of cure” and if we apply this to global healthcare systems, then we must focus on early prevention if we are to see long-term, sustainable change.

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We’re getting too old for this
Global healthcare systems, including the US, are suffering at the hands of an aging population. Advancements in medicine, although welcome, are allowing individuals to live longer lives, which in turn, means that more people are calling upon the services of the healthcare and social care sector.
Exacerbated by the hardships of the pandemic, hospitals and care homes are operating well beyond capacity and many clinicians are also vastly overworked and unable to deal with the excess demand. As a default, humans are wired to action any sense of discomfort or abnormality with a trip to the doctor, however, a lot of older adults find themselves becoming more anxious about the medical setting as the years go on. This can actually often cause them to refrain from seeking support, which inevitably in the long run, will mean that treatment is insisted on further along the disease cycle. If an AI platform allowed for regular monitoring either within the social care setting or at home, this would not only reduce anxiety, but also provide a sort of “check engine” light for the human body.
Of course, the need for this technology is not exclusive to the elderly population and its application in everyday life would ultimately lead to a better informed population which only calls upon medical professionals when they are actually needed.