This research develops an innovative AI biomarker system that combines multiple data sources to detect cancer cachexia earlier than traditional methods.

• Integrates lab reports, CT scans, and clinical notes through multimodal AI analysis
• Addresses the challenge of having no single definitive biomarker for this complex syndrome
• Creates a comprehensive detection approach for a condition characterized by muscle wasting and metabolic dysfunction
• Potential to significantly improve quality of life and reduce mortality in cancer patients

This advancement matters because earlier cachexia detection enables timely interventions in cancer treatment plans, potentially extending survival and improving patient outcomes.

Multimodal AI-driven Biomarker for Early Detection of Cancer Cachexia