When clinicians can't quickly parse a foreign patient's multilingual referral records, diagnostic accuracy is at risk. Upstage Studio parses medical documents to extract structured clinical content, and an LLM node can organize key findings—HPI, surgical history, allergies—into a timeline format. Clinicians get a faster starting point for understanding a patient's history across language barriers.

Varying medical record formats across countries and complex clinical terminology make it difficult for clinicians to consistently parse patient information. Upstage's Solar LLM is trained on medical terminology and can convert records from English, Chinese, Japanese, and other languages into a standardized summary format. This reduces time spent manually comparing multiple source documents.

Manually searching through extensive overseas clinical papers for specific findings is highly inefficient. When an LLM node is connected, clinicians can ask natural language questions within the extracted document set and receive answers grounded in the source content. This supports faster clinical decision-making without requiring a full manual review of every record.