Clinical Application of Automated Interpretation System for Chest X-Ray Images Based on Multimodal Large Models

In this prospective study, the quality of reports generated by junior radiologists was assessed using a 5-point Likert scale titled "Radiology Report Quality Assessment Scale", where the minimum value is 1 and the maximum value is 5, with higher scores indicating better report quality. These scores were compared between the AI-assisted group (junior radiologists using AI tools for report generation) and the standard care group (junior radiologists generating reports without AI assistance).

In this prospective study, the agreement between reports generated by junior radiologists and standard reports was assessed using the RADPEER scoring system-a peer review program established by the American College of Radiology (ACR) designed to evaluate the interpretation accuracy of radiologists-where the degree of concordance is measured by grading discrepancies and agreements according to specific criteria that also account for the clinical significance of differences. The RADPEER system uses a 5-category scale with a minimum value of 1 and a maximum value of 5, where higher scores indicate greater agreement between the generated reports and standard reports.

In this prospective study, the preference between reports generated by junior radiologists in the AI-assisted group versus the standard care group was evaluated using the "Expert Pairwise Preference Assessment Tool", a structured measurement tool designed to quantify expert consensus on report superiority. The assessment was conducted by a panel of 5 independent radiology experts, who reviewed paired reports (one from the AI-assisted group and one from the standard-care group for the same clinical case) and individually indicated their preference for which report was more clinically valuable, accurate, or comprehensive. The unit of measure for this outcome is the "Percentage of paired cases with majority expert preference", defined as cases where ≥3 out of 5 experts expressed a clear preference for either the AI-assisted or standard care report.

The time from when radiologists began examining chest radiographs to the completion of final reports, comparing efficiency between the AI-assisted and Standard-care groups.

In this retrospective study, the quality of reports generated by Janus-Pro-CXR, Janus-Pro, and ChatGPT 4o (compared to standard reports) was assessed using the 5-point Likert scale titled "Radiology Report Quality Assessment Scale". The scale has a minimum value of 1 and a maximum value of 5, with higher scores indicating better report quality.

In this retrospective study, the agreement between reports generated by Janus-Pro-CXR, Janus-Pro, and ChatGPT 4o and standard reports was assessed using the measurement tool titled "RADPEER Scoring System"-a structured peer review system established by the American College of Radiology (ACR) for evaluating radiological interpretation accuracy. The RADPEER system uses a 5-category scale with a minimum value of 1 and a maximum value of 5, where higher scores indicate greater agreement between the generated reports and standard reports.

In this retrospective study, the preference between reports generated by Janus-Pro-CXR, Janus-Pro, and ChatGPT 4o (compared to standard reports) was evaluated using the "Expert Pairwise Preference Assessment Tool"-a structured measurement tool designed to quantify expert consensus on report superiority. The assessment was conducted by a panel of 5 independent radiology experts, who reviewed paired reports (matching reports from a model-generated report vs. a standard report for the same clinical case) and individually indicated their preference based on predefined criteria including clinical accuracy, completeness, clarity, and diagnostic utility. The unit of measure for this outcome is the "Percentage of paired cases with majority expert preference", defined as cases where ≥3 out of 5 experts expressed a clear preference for one report over the other.