About this episode

Dr. Siddhant Dogra and Dr. Su Hwan Kim discuss the impact of reader experience on AI-assisted brain MRI diagnosis.

Dr. Siddhant Dogra sits down with Dr. Su Hwan Kim to discuss how reader experience influences the performance and real world utility of large language models for brain MRI differential diagnosis. Together they explore AI assisted decision making, automation bias, radiology training, and why strong AI performance does not always translate into meaningful clinical benefit. Performing Best When Needed Least: Reader Experience ShapesAccuracy Gains in Large Language Model–assisted Brain MRIDifferential Diagnosis. Schramm et al. Radiology 2026; 319(2):e253477.

People in this episode

Host: Dr. Siddhant Dogra

Guest: Dr. Su Hwan Kim

Topics covered

• AI assistance
• reader experience
• brain MRI
• differential diagnosis
• radiology training
• automation bias

Keywords

• AI
• radiology
• MRI
• differential diagnosis
• automation bias
• clinical benefit
• large language models

Mentioned in this episode

Organizations: Radiology

Books & works: Performing Best When Needed Least: Reader Experience Shapes Accuracy Gains in Large Language Model–assisted Brain MRI Differential Diagnosis

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