In the face of increasingly sophisticated and more frequent cyberattacks that threaten the sensitive data of all healthcare providers, vRad is continuously advancing our systems to predict, prevent, and respond to these threats. The latest milestone in our commitment to safeguard patient information and other sensitive data is our achievement of SOC 2 Type II compliance.
Originally published by Michael Walter on Radiology Business
In radiology, it is vital for radiologists to connect with the entire patient care team in a seamless and timely manner.
Imaging providers have done this over the years through such tools as land lines, pagers, fax machines and integrating with the electronic medical record (EMR). Some radiology practices even have their own secure client portal for this very purpose.
But times are changing. Communication among healthcare providers is more complicated now than ever. Radiologists are working on a broader array of technology platforms from diverse locations, including from home. Care teams are getting larger with an increasing need for near real-time communication. The old ways of delivering radiology results are imperfect for this new era of modern medicine. One dropped connection or wrong number can cause wasteful delays and even harmful outcomes.
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.
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.
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.
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