Tempus Cancer Model Boosts Survival Prediction AUC with 1.67M Patient Dataset
neuroecology · x · 2026-08-27
Tempus introduced the oFM (Oncology Foundation Model), a multimodal foundation model trained on a real-world cohort of 1.67 million cancer patients. It fuses clinical trajectories with DNA, RNA, and H&E pathology images into a unified patient-state embedding.
Key Results:
- In prognostic benchmarks, the oFM improved the Area Under the Curve (AUC) for overall survival prediction from 0.563 to 0.774, significantly outperforming expert-curated clinical and molecular feature baselines.
- Across 11 comparative-treatment cohorts, oFM embeddings improved treatment-benefit ranking in 9 cohorts, achieving a three-fold higher pooled and scale-normalized treatment-benefit AUTOC than baseline features.
Technical Details:
- The model encodes daily clinical and molecular episodes and integrates them over time alongside pathology images.
- The study utilized over one million patients for training with strict patient-level partitioning for validation and testing.
More from Research
- Study Finds Friction in 49.7% of Human-AI Conversations, Reveals Effective Recovery Strategies — EchoShao8899 · 2026-08-27
- Skild robot learns to make pancakes from one video, mastering in-context learning — deepakpathak · 2026-08-27
- Perceptron Releases Isaac 0.5: 36B Open Weight Embodied Foundation Model — lukas_m_ziegler · 2026-08-27
- Ai2 helps build 47B-token Thai corpus with Dolma toolkit — allen_ai · 2026-08-27
- SPC backs Deep Cogito: $3.5M to match frontier models — adityaag · 2026-08-27
- Benchmark: Brute force outperforms HNSW at 5,183 documents — thehuhcoder · 2026-08-27