Artificial intelligence in healthcare – great fear but even greater potential!
The rapid commercialization of machine learning and big data has helped bring Artificial Intelligence (AI) to the forefront of healthcare, giving it the capacity to change how the industry treats patients holistically. AI’s potential ranges from IT tools that can interpret images impressively faster and better than their human counterpart, to devices that help patients to establish more accurate diagnoses, before they see a physician.
However, the widespread technological and regulatory restrictions the technology currently faces mitigate it’s potential to be a disruptive force, at least in the short term.
Ongoing discussions around data and job security pose challenges that go beyond the healthcare ecosystem and affect societies as a whole. The major challenges for AI in healthcare are:
· Lack of acceptance,
· Lack of experts,
· Missing budget, and
· Difficult collection and harnessing of data (to train the AI based solutions).
Even though the application areas of AI are limited at the moment, hospitals deploying the technology certainly have the potential to achieve significant efficiency gains and cost reductions, including a substantial improvement of healthcare provision. Moreover, the application of AI in healthcare can lead to:
· More reliable – and faster - diagnoses,
· Enhanced data management, and
· Strong reduction of bureaucratic burden and mistakes.
AI‘s benefits are increasingly well understood by healthcare stakeholders in theory, however for AI technologies to achieve mainstream traction, the healthcare sector needs to reach a certain level of digitization first – and this holds true for the majority of European countries, who have demonstrated very slow adoptions in the field of digital health.
For more information on the potential of AI in healthcare, please click here (license required).