Objective:

To create and authenticate a bilingual LLM-based instrument that transforms oncology radiology reports into comprehensible English and Hindi for patients, while preserving diagnostic accuracy and emotional nuance.

Approach:

Key Findings:

• Average rubric scores for accuracy, language clarity, and readability were 4.77 ± 0.62, 4.78 ± 0.56, and 4.9 ± 0.32, respectively.
• Complete core diagnostic information was maintained in all reports.
• Readability improved significantly, with Flesch Reading Ease scores increasing from 49.2 to 73.
• Empathy expressions in both English and Hindi were deemed appropriate.

Interpretation:

The bilingual AI-powered framework enhances the clarity and comprehensibility of oncology radiology reports.

Limitations:

• The study was limited to a single site and specific cancer type, which may affect generalizability.
• Potential issues with LLMs such as hallucinations and contextual inaccuracies were acknowledged.

Conclusion:

The tool demonstrates the capability of secure, patient-focused communication aligned with personalized medicine objectives.

Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.