Dr. Meyer, what does “integrated healthcare“ mean?
Dr. Michael Meyer: The term “integrated healthcare” refers to a form of healthcare that is characterized by a high degree of collaboration among multiple disciplines and healthcare sectors. Integrated healthcare aims to increase the quality of care through interdisciplinary and interprofessional collaboration between multiple health care providers and across sectors, as well as explore cost-effectiveness in healthcare. The interaction between radiology, pathology and the laboratory is yet another facet of integrated healthcare.
What role does artificial intelligence play in this setting?
Meyer: Artificial intelligence is a broad term that’s rather vaguely defined. Anyone referring to AI these days typically means “deep learning”, a subset of machine learning based on artificial neural networks. The term became more widely known thanks to the Google algorithm that defeated the world's number one Go player. In reality, neural networks have been around for decades. What has primarily changed though is the increased computing power. As a result, algorithms that have existed for some time can now also be used in practice. Graphics processing units have also become significantly more powerful – they are key tools to train neural networks.
Applications of AI are designed to improve clinical processes and help doctors, but are not intended to replace them. Feedback from our customers has shown that the use of AI improves the quality of care and results in lower discrepancy rates in AI-supported findings. It also assists radiologists with routine tasks such as measuring pulmonary nodules or aortic cross-sections, freeing up more time to devote to each patient. The result is patient-friendly precision medicine.
What are the potential benefits of integrated healthcare as it pertains to the treatment of each patient?
Meyer: Patients benefit from personalized diagnostics and therapy. They receive the right care at the right time thanks to the expansion of precision medicine. Intelligent algorithms can already create an accurate digital twin of specific patient organs. This, in turn, facilitates personalized risk assessments and treatment simulation. In the long term, we hope that it will be possible to create a fully functional digital twin of the entire body.