Routine laboratory trajectories encode the onset of organ-level complications in cancer
Researchers have developed a transformer model capable of predicting the onset of organ-level complications in cancer patients up to two years in advance. The model analyzes longitudinal laboratory measurements, capturing temporal physiological changes that single-timepoint tools miss. This approach demonstrated significant enrichment in predicting 162 complications across multiple myeloma and ovarian cancer patients, with predictions showing transferability to independent healthcare systems. AI
IMPACT Enables proactive patient monitoring and intervention for cancer treatment complications, potentially improving outcomes and reducing healthcare costs.