Radiology

Radiologists and healthcare administrators have been waiting a long time for the arrival of promised AI tools for radiology. Most AI applications used by radiology providers today are focused on worklist prioritization. While improving the speed of patient care is incredibly important, recent strides in quality improvement open a new world of possibility.

Because I work as a teleradiologist, I (thankfully) no longer have to commute to get to work. Living in southern California, traffic is one of the things I do not miss at all. I used to spend a lot of time behind the wheel driving to the hospital where I worked, thinking of ways I could make my commute faster and more efficient. Admittedly, I’m a bit obsessive when it comes to time and efficiency, especially in the way I work.

Behind the scenes, it takes a lot of complex technology and sophisticated software to make an advanced reading platform run so seamlessly. At vRad, our incomparable team of technologists and programmers are developing some of the most advanced applications in the medical industry, all with the goal of empowering radiologists to practice radiology free from unnecessary interruptions, distractions, logistical hurdles, and administrative burdens.

For the latest information on vRad’s Artificial Intelligence program please visit vrad.com/radiology-services/radiology-ai/

Accelerating care delivery

I am pleased to share that vRad has deployed two additional Artificial Intelligence (AI) models to our imaging platform, bringing the total to seven active models helping patients right now.

The first new model identifies pneumoperitoneum in chest CTs, and the second model identifies testicular torsion in ultrasound scans. Both conditions are critical, and timely diagnoses will have a positive impact on patient outcomes. As with all our innovation and product development, our models are immediately available to clients as part of our AI-enhanced on-the-ground and in-the-cloud radiology solutions.

After 11 years as a vRad radiologist – 3 of them as Clinical Chief of Abdominal Imaging – I left in 2019 for a teleradiology position at another well-known national practice. Just 9 months later, I’m back. Here’s why.

For the latest information on vRad’s Artificial Intelligence program please visit vrad.com/radiology-services/radiology-ai/

vRad AI models are at work today prioritizing critical cases like strokes, improving reporting speed and accuracy, and assisting billing compliance. Below, neuroradiologist Josh Morais, MD recalls how AI helped promptly identify a stroke victim in need of immediate treatment, and offers his perspective on the daily impact he sees from AI.

vRad's massive, diverse dataset is an incomparable real-world testing ground for validating radiological AI models. Following is an excerpt of Brian Baker’s comments from a recent interview in The Imaging Wire.

For the latest information on vRad’s Artificial Intelligence program please visit vrad.com/radiology-services/radiology-ai/

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.