Laying the Groundwork for an AI Breakthrough
Digital transformation requires a clear vision, buy-in at every level, and significant investment. Here are three steps to streamline the process.
Digital transformation requires a clear vision, buy-in at every level, and significant investment. Here are three steps to streamline the process.
Anthony Fernando, CEO and president of Asensus Surgical, discusses the potential benefits of augmented intelligence in robotic surgery for both patients and physicians.
As data, rather than document-based dossiers, become the focus for regulatory processes, regulatory affairs managers need to consider whether team skill sets need to be refreshed to reflect new ways of working.
Bringing design and quality assurance processes together earlier in the device development process can reduce costs and nonconformances, while improving outcomes.
On Tuesday, October 4, the White House released a Blueprint for an Artificial Intelligence (AI) Bill of Rights geared toward protecting the American public as the use of AI and machine learning expands throughout industry and online.
The deeper insights provided by a single source of truth help regulatory teams pinpoint and address gaps in data collection during each trial phase. By mitigating potential risks earlier in the process, teams generate more robust evidence and stronger submissions, which often means a shorter approval process.
The reality of biased data is becoming all too clear, which raises important questions for clinicians as well as device and drug developers. In a world full of biased data what are the most ethical practices to achieve equitable health care?
Artificial intelligence has numerous practical applications in diagnostic imaging; the key to making them work for clinicians and patients lies in developing and embracing integrated workflow networks.
Peter O’Blenis, CEO of Evidence Partners, discusses the growing role—and challenges –of literature reviews in the medtech market.
Remote care in the home relies both on the quality of patient monitoring and on the insights provided to the care team. There is a real danger that data overload and alert fatigue will undermine otherwise well-designed remote patient monitoring (RPM) and Hospital at Home programs. The software platform and algorithms tasked with integrating and evaluating data must identify the data that matters, when it matters.