Summary:
«Many AI algorithms are already available to support diagnosis, make image interpretation more efficient, augment clinical decision-making, inform procedural interventions and therapies, and even support utilization management and authorizations.»
«However, the power of AI in diagnostic imaging is frankly underused. The reason for this underutilization is that many of these AI models work in silos: They’re not integrated into the radiology workflow in ways that make them usable or useful.»
«But that’s changing. Today, integrated workflow networks transform how radiologists and other imaging stakeholders can use AI to improve clinical and financial outcomes as well as the radiology experience.»
«What’s particularly valuable about an integrated workflow network is not the AI models that support earlier diagnosis, nor is it the enhanced collaboration and sharing that can happen seamlessly between providers and patients. Rather, the true value in these networks is the real, end-to-end patient care solutions that are emerging.»
Article written by Dr. Sheela Agarwal
01|06|2022
Source:
HealthTech