Two components are essential to successfully establish, develop and sustain applied AI in radiology: Uncompromised collaboration between radiologists and computer scientists, and access to a constant flow of data that is representative of a highly diverse population. This is the foundation of vRad Radiology AI.

Many radiology practices talk about visionary AI, but there are only a few implementing AI into their workflows.

At vRad, AI is helping manage regulatory compliance and adherence to best practices to ensure quality care, which should avoid unnecessary medical expenses and mitigate malpractice risk.

Our AI models are at work today prioritizing critical cases, improving reporting accuracy and assisting billing compliance. But we’re just getting started. AI will permeate the practice and business of medical imaging to empower radiologists, conquer mountains of administrative burden and strengthen health care delivery.

Early hype implied that artificial intelligence would replace radiologists. Turns out the opposite is closer to the truth. Without radiologists there is zero potential for the future of AI in diagnostic imaging. Radiologists are integral to model development, testing and validation.

While workflows change to balance growing demand for imaging studies with decreasing capacity, it is essential that patient care is not compromised. Radiology practices must be prepared to invest and adapt for the long term to ensure critical performance metrics remain solid in this volatile environment.

The demand for imaging studies is expected to continue to increase for the foreseeable future. However, the number of radiologists on hand to perform those studies will remain relatively flat, and potentially decline. This is creating a market-wide capacity imbalance that is straining performance across radiology.

For me, the collegiality of the practice of radiology is a highlight of my daily work. When I first considered leaving a traditional practice for teleradiology, I was worried that working remotely would leave me feeling disconnected. In actuality, I’ve never felt more engaged in a supportive and interdependent team committed to delivering quality patient care.

Moving past the initial media hype, practitioners are beginning to demonstrate how AI applications can enhance the ability of radiologists to support better patient outcomes.