Roman Boimystryuk, Quality Manager for CT Data Annotation, medDARE
The adoption of artificial intelligence (AI) in medical imaging is no longer a vision of the future — it’s a present-day reality for many radiologists. But just how integrated is AI into their daily workflows? And where do experts see it making the most impact in the coming years?
We gathered insights from practicing radiologists who work on medDARE’s data annotation projects to understand how AI is currently supporting their work and which medical challenges they believe AI can help solve.
AI in Daily Radiology Practice: From Optional to Essential
Several radiologists shared that AI has already become an indispensable part of their day-to-day routine, especially in high-volume diagnostic centers:
“I work at a regional oncology dispensary and we perform dozens of multiphase CT and MRI scans every day. AI helps us analyze these images faster and more thoroughly, especially when tracking disease progression and treatment response.”
— Olena Voronovska, Data Collection Assistant
Others described using AI tools for automated tumor volumetry, lung nodule detection, and MRI prostate segmentation:
“I use AI daily for precise tumor measurements, lung nodule detection — even small ones that might be missed due to fatigue — and Pi-RADS classification assistance. It saves time and helps minimize manual errors.”
— Olena Voronovska, Data Collection Assistant
Our Quality Manager for CT Data Annotation, Roman Boimystryuk noted:
“AI in radiology optimizes time and minimizes mistakes. Tasks like volumetric measurement of pathological tissue versus normal tissue are now automated and almost instant.”
Olena Voronovska, Data Collection Assistant, medDARE
What’s Coming in the Next 3–5 Years?
The consensus is clear: AI will rapidly expand in diagnostic medicine over the next few years. Radiologists predict:
- Deeper integration into image analysis, particularly in radiology, MRI, and CT
- Personalized medicine — AI tailoring treatment plans based on genetic and clinical data
- Virtual assistants for doctors — helping with documentation, triage, and case summaries
- End-to-end patient support — from symptom onset to post-treatment monitoring
“I see AI embedded across the medical journey: from first symptoms to diagnosis, therapy monitoring, and follow-up. Emergency medicine will likely see the fastest development — where every minute matters.”
— Olena Voronovska, Data Collection Assistant
What Problems Should AI Solve Next?
When asked what pressing problem AI should solve today, nearly all radiologists pointed to early cancer detection.
“In Ukraine, many cancer diagnoses occur at stages III or IV. AI could save lives by analyzing data early — symptoms, labs, imaging — and prompting timely screenings or referrals right from the family doctor’s interface.”
— Olena Voronovska, Data Collection Assistant
Others hope AI can one day even discover treatments for the world’s most serious diseases:
“If I could solve one problem, I’d want AI to help find a cure for cancer and HIV.” – Quality Manager for CT Data Annotation, Roman Boimystryuk
Final Thoughts
From assisting with complex measurements to detecting subtle abnormalities, AI is becoming an essential diagnostic companion for radiologists. While adoption varies across clinics and regions, the trend is unmistakable — medical professionals are turning to AI not only to optimize workflow efficiency, but also to improve diagnostic accuracy and patient care.
At medDARE, we specialize in collecting and annotating real-world medical data — including CTs, MRIs, and surgical videos — with clinical precision and full compliance (HIPAA, GDPR, ISO-certified). Whether you’re developing an early detection tool or scaling your diagnostic AI solution, we help ensure your model is trained on data that’s clean, structured, and medically validated.
👉 Looking for annotated datasets or support with data collection? Let’s talk!
