It is clear that the application of AI within healthcare is here to stay. Part of the AI research Omdia been conducting over the last two years has been focused on machines developed primarily for medical diagnostics and drug discovery, with our most recent reporting now covering more than $8 billion in venture funding for 363 machines and counting...

It is clear that the application of AI within healthcare is here to stay. Part of the AI research Omdia been conducting over the last two years has been focused on machines developed primarily for medical diagnostics and drug discovery, with our most recent reporting now covering more than $8 billion in venture funding for 363 machines and counting, 28% of which now have regulatory approval (FDA, CE, MFDS, CFDA). This is up 15% from last year, and signals that the development community is pressing forward despite some lingering obstacles.

Two of these key market inhibitors are a lack of large-scale clinical validation and clear, demonstrated ROI. And solving the ROI issue will likely remain problematic as there is still no direct reimbursement for using AI as a diagnostic tool, coupled with the fact that accounting departments consider AI as an indirect expense. So, identifying exactly how AI can be applied to benefit healthcare organizations, payers, clinicians, and patients is an ongoing topic of much discussion – One which needs to emphasize value, workflow integration, and efficacy. The most recent infographic from Omdia highlights machines designed for diagnostic applications that now have regulatory approval.

Click on the image on the right to access the infographic.

 

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