Reimagining the infrastructure of cancer care

If there’s a question I hear most often from researchers it’s: How can we trust real-world data extracted by AI?

New research showcases the impact of large language models from extracting nuanced clinical information from unstructured data sources to successfully building digital twin models that simulate patient outcomes under different treatment scenarios

When building a comparative effectiveness study or modeling long-term survival, health economics and outcomes research (HEOR) teams face a familiar problem: treatment pattern data derived from electronic health records (EHRs) tells you who the patient is clinically, and what happened, but historically not why.

Three-pillar framework sets methodological benchmark for data quality and transparency in oncology data