X-rays are among the most common imaging exams in health care. They're also central to some of the decisions clinicians make every day, from evaluating a suspected fracture in the emergency department to identifying abnormalities on a chest X-ray that may require further investigation.
For radiologists, the challenge isn't simply identifying what's on an image. It's interpreting a high volume of exams, recognizing potentially subtle findings, managing competing priorities and communicating information that helps guide patient care.
AI can help. But as health systems introduce more algorithms into radiology, there's another consideration: How do you make those capabilities useful without adding complexity to an already demanding workflow?
At RapidAI, we believe the answer goes beyond the algorithm itself. It's about bringing clinical AI into the environments where radiologists work and connecting its insights to the teams responsible for what happens next.
That's the thinking behind our latest integration with AZmed.
AZmed's FDA-cleared AZtrauma and AZchest applications, part of its Rayvolve AI suite, bring additional X-ray analysis capabilities to the Rapid Enterprise™ Platform.
AZtrauma detects fractures, joint effusions and dislocations on musculoskeletal X-rays in adult and pediatric patients ages 2 and older in the U.S. AZchest analyzes frontal chest X-rays for five findings: lung nodules, consolidation, pneumothorax, pleural effusion and increased cardiothoracic ratio. It also provides triage and notification for pneumothorax and pleural effusion.
These capabilities can provide valuable support to radiologists. But making another AI algorithm available is only part of the opportunity.
Through Rapid Navigator Pro, radiologists can access AZmed results and worklist prioritization alongside other AI findings within a consistent reading environment.
Instead of navigating another standalone application, radiologists can incorporate these insights into their existing workflow, helping them manage priorities and maintain focus on the interpretation and clinical judgment that matter most.
The goal isn't to add more technology to the radiologist's day. It's to make the technology they use work better together.
A radiologist's interpretation often informs decisions well beyond the reading room.
A suspected fracture may require an orthopedic consultation. A chest X-ray finding may influence an emergency physician's next steps. An incidental lung nodule may warrant additional evaluation or follow-up.
In each case, timely access to relevant information matters.
Through the Rapid Enterprise Platform, AZmed results are also available to emergency physicians and orthopedic teams in the Rapid Mobile App.
This gives clinicians access to AI findings within a familiar clinical workflow, helping support communication and coordination around patient care.
It's an important distinction in how we think about clinical AI. The value doesn't end when an algorithm identifies a potential abnormality, or even when the radiologist completes the read. It extends to how that information supports the people making decisions throughout the patient journey.
And that doesn't diminish the radiologist's role. It reinforces the importance of connecting radiology expertise to the broader care team.
As health systems expand their AI programs, the number of available algorithms continues to grow. But adding solutions individually can introduce fragmented workflows, additional infrastructure requirements and new challenges in managing performance and adoption.
Health systems need more than access to AI. They need a way to make it work together.
The Rapid Enterprise Platform brings RapidAI-developed and third-party clinical AI into connected workflows, supported by shared infrastructure and centralized oversight.
With Rapid Edge Cloud supporting deployment and Rapid Insights providing visibility into AI utilization and performance, organizations can expand their clinical AI capabilities while maintaining a more consistent approach to managing them.
For radiologists and care teams, that means accessing relevant tools through familiar environments. For health system leaders, it means building on an enterprise foundation rather than managing an expanding collection of disconnected solutions.
The addition of AZmed's X-ray applications extends the Rapid Enterprise Platform's capabilities across another important area of imaging, building on more than 50 RapidAI-developed and third-party clinical solutions spanning neurology, cardiac and vascular, trauma, and oncology care.
But the bigger story isn't the number of algorithms.
It's what becomes possible when those capabilities work together to support the people interpreting images, communicating findings and making treatment decisions.
For radiologists, that means AI support integrated into the read. For clinicians, it means access to relevant insights that can help inform the next step in care. And for health systems, it means a more connected way to expand clinical AI across specialties.
Because the future of clinical AI isn't just about what technology can detect. It's about how well it supports the people responsible for patient care.
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In the U.S., AZmed’s AZtrauma detects fractures, joint effusions and dislocations on musculoskeletal X-rays in adult and pediatric (ages ≥2) populations. AZchest covers five findings on frontal chest X-rays: lung nodules, consolidation, pneumothorax, pleural effusion and increased cardiothoracic ratio, with triage and notification for pneumothorax and pleural effusion.
Radiologists receive AZmed results and worklist prioritization in Rapid Navigator Pro. Emergency physicians and orthopedic teams access results in the Rapid Mobile App, giving them shared clinical context to coordinate next steps.
No. Health systems can add and manage AZtrauma and AZchest through a single IT deployment of the Rapid Enterprise Platform.