Evidence synthesis often relies on quantitative data embedded in Kaplan-Meier curves, forest plots, and other scientific figures. Extracting this information manually can be time-intensive, inconsistent, and difficult to scale.
AI-native approaches combine multimodal AI and computer vision to extract graphical evidence and transform it into structured, analysis-ready data. Their value depends on rigorous validation, governance, and human oversight.
Download Read the Unreadable: AI-Native Evidence Synthesis from Forest Plots, Kaplan-Meier Curves, and Beyond to explore how AI can unlock quantitative evidence from scientific figures and support faster, more comprehensive evidence synthesis.
