KLAS Research’ recent report on “Artificial Intelligence in Imaging 2020” addresses both the opportunities and the challenges of AI adoption and focuses on best practices
Data-driven healthcare can be broken down into three distinct pillars: the use of data by patient and practitioner; the regulation of data to ensure privacy and security; and the innovations that are driving the creation of this data.
The evolution of artificial intelligence (AI), deep learning, machine learning, automation and the Internet of Things (IoT) has seen technology adapt to new models of operation and introduce new ways of thinking and doing business.
Physician burnout is a deeply concerning issue for hospitals and across the healthcare sector in general, physicians feel burnt out and feel they cannot keep up with job demands.
Artificial intelligence (AI). It’s become so prevalent and capable that it’s almost as if every conversation is peppered with its potential. In the healthcare industry,
Radiology leaders in the United States are focusing heavily on the potential for artificial intelligence to deliver quality and efficiency augmentation. We recently hosted a
Diagnostic imaging AI is fast becoming a measurable advantage for the radiology practice that wants to shift gears and gain market traction.
AI is transforming the world of healthcare, it has become a powerful tool to assists practitioners in their daily work. There are many examples of real-life artificial intelligence already in use in healthcare.
Jacob Platin, Christopher Ye, Charles An – Aidoc A.I. Software Engineering Interns Every summer, Aidoc hosts international interns who have the opportunity to take on
Christopher Ye, Jacob Platin, Charles An – Aidoc A.I. Software Engineering Interns Every summer, Aidoc hosts international interns who have the opportunity to take on
How the use of AI in the emergency room is aiding physicians in triaging
On the use of Pulmonary Embolism Guidelines and the intersection with AI