Browsing: Insights

X-ray imaging has been a cornerstone of diagnostic medicine for decades, providing a non-invasive way to visualize internal structures. From detecting fractures and foreign objects to monitoring diseases like pneumonia and cancer, X-ray systems play a vital role in patient care.

This may be the right time to apply AI in your healthcare organization. You could be faced with care coordination challenges unlike any other. A new payment structure calls for a new AI-driven workflow.

Imagine this: A team member is consistently late for their shift, delaying patient imaging schedules. Or perhaps there’s a pattern of repeat scans due to positioning errors, impacting patient care and department efficiency. As a radiology leader, addressing these issues isn’t optional – it’s necessary.

This allowed me to narrow the subject matter to relevant issues encountered by biomedical engineers and field service engineers working on a variety of equipment. Although I researched this article from the view of an ultrasound engineer, I believe the problems encountered go beyond just ultrasound.

One often overlooked area of talent acquisition is neurodiversity in radiology – hiring individuals with diverse neurological profiles, including autism, ADHD, dyslexia and other conditions. 

The MRI technologists that I have had the opportunity to get to know over the course of my career all agree on one thing: implant research is a very complex, time consuming, daunting task that gets more imposing every day, since the healthcare industry is implementing new devices continuously.

Having a diverse workforce is critical to advancing innovation, collaboration and patient care in healthcare, particularly in radiology departments. Yet too often, our efforts become knee-jerk reactions – a scramble to recruit broadly from underserved populations without first reflecting on the specific gaps in our teams.