This research introduces specialist language models tailored specifically for oncology to overcome the limitations of general-purpose LLMs in clinical settings.

• Addresses challenges with unstructured clinical data including inconsistencies and ambiguities
• Creates domain-specific reasoning capabilities for cancer terminology and context-dependent interpretations
• Enables cross-lingual functionality for broader application across healthcare systems
• Supports multi-modal data integration to process diverse clinical information sources

Significant for healthcare as it promises to transform raw clinical oncology data into reliable, actionable insights for improved cancer care decision-making and treatment planning.

Towards Scalable and Cross-Lingual Specialist Language Models for Oncology