Radiology AI in Routine Practice
Real-world deployment reveals adoption gaps and varying engagement with regulator-approved artificial intelligence decision support tools
By
Conexiant News Staff
February 17, 2026
Clinical Scorecard: Radiology AI in Routine Practice
At a Glance
Category Detail
Condition Radiology workflow enhancement Key Mechanisms AI decision support tool for flagging potential findings on CT imaging Target Population Radiologists in clinical settings Care Setting Tertiary referral hospital
Key Highlights
AI tool influences radiology workflow but with varied real-world impact Engagement with the AI system varies among clinicians and contexts Barriers include information overload and uncertainty about medicolegal liability Implementation is an ongoing process requiring continuous evaluation Need for clearer communication regarding system limitations Guideline-Based Recommendations
Diagnosis
Integrate AI tools into clinical operations for enhanced diagnostic support Management
Address interoperability challenges and workflow disruptions during AI tool use Monitoring & Follow-up
Conduct ongoing evaluations of AI system performance and user engagement Risks
Mitigate risks related to medicolegal liability and accountability Patient & Prescribing Data
Patients undergoing CT imaging studies
AI can assist in identifying potential findings, especially during high workload periods
Clinical Best Practices
Foster sustained engagement from radiologists with AI tools Establish clearer governance structures for AI implementation Provide training to address information overload and system limitations Related Resources & Content
