The long-standing frustration of healthcare systems—where sophisticated data often sits dormant while clinicians drown in paperwork—has finally met its match in the rise of agentic technology. This paradigm shift marks the transition from passive artificial intelligence that merely suggests actions
Traditional federal regulatory structures are poorly equipped to handle dynamic technologies that continue to learn and evolve after they have been deployed into clinical settings. This gap is becoming increasingly apparent as the American healthcare landscape undergoes a radical transformation,
James Maitland brings a wealth of experience to the intersection of robotics and healthcare technology. As an expert in health informatics, he has spent years navigating the complex landscapes of IoT and clinical data science. Today, we sit down to discuss a transformative shift in how we handle
A mid-study hardware or software upgrade at a clinical site can silently rewrite longitudinal data by increasing the contrast-to-noise ratio, potentially masking or mimicking a drug effect. This technical volatility represents one of the most significant yet underappreciated risks in modern drug
Mandatory equity-impact evaluations are necessary to determine how new algorithmic tools will affect different demographic groups before deployment. The current pace of technological advancement has left public health frameworks struggling to keep up with the volume of digital integration occurring
Michigan Medicine became the first United States healthcare system to successfully implement a DICOM-based digital pathology PACS within a broader enterprise imaging network. This milestone signifies a major shift where pathology is no longer treated as an isolated laboratory function but as a
