Soombit.ai’s GenAI improves chest x-ray reporting accuracy while reducing reading time, optimizing radiologists’ workflow.
A South Korean study validated Soombit.ai’s GenAI model, AIRead, demonstrating its ability to improve chest x-ray reporting accuracy while significantly reducing radiologists’ reading times. The findings highlight GenAI’s growing role in streamlining medical imaging workflows.
In a real-world study, five radiologists used AIRead to interpret 758 chest x-rays. The AI-generated preliminary reports reduced reading times by 42% and improved diagnostic sensitivity for conditions like widened mediastinal silhouettes and pleural lesions. AIRead also increased agreement among radiologists, ensuring greater consistency in reports. By automating detailed preliminary reports, the AI allowed radiologists to focus on complex cases while maintaining high accuracy.
Unlike traditional AI models, AIRead generates comprehensive reports that influence radiologists’ interpretations, helping standardize terminology across cases. However, the model currently lacks the ability to compare findings with prior x-rays or incorporate broader clinical context. Despite these limitations, radiology experts view GenAI-assisted reporting as a breakthrough in medical imaging, improving efficiency without compromising accuracy.
Soombit.ai’s AIRead represents a major advancement in diagnostic AI, enhancing radiologists’ workflows and reducing workload. As the model evolves to integrate historical comparisons and patient context, it is expected to become a vital tool in medical imaging, supporting faster and more precise clinical decision-making.