Five-agent AI team could speed clinical trial design using real-world patient records

An artificial intelligence system that operates like a collaborative team of medical experts could accelerate clinical trial ...
Communications of the ACM

Can We Understand How Large Language Models Reason?

Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...
IEEE

Integrating LLMs and Knowledge Graphs for Medical AI: Advances, Challenges, and Future Directions

Abstract: This review synthesizes how integrating large language models (LLMs) with knowledge graphs (KGs) advances medical AI across methods, applications, and evaluation. While LLMs excel at natural ...

The Web Is Growing A Second Layer – Almost A Third Head

Google shipped two new specs weeks apart. Here's what OKF and ARD actually do, how they differ from LLMs.txt and MCP, and ...

Build An OKF Brain Like Mine!

Discover how I built my OKF brain and the transformative impact of the Open Knowledge Format on the agentic web.
Journal of Medical Internet Research

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

The resulting knowledge graph provides a robust framework for understanding sepsis, supporting clinical decision-making, and facilitating further research. The success of this approach underscores the ...
GitHub

[ICCV2025] CleanPose: Category-Level Object Pose Estimation via Causal Learning and Knowledge Distillation

Official implementation of our CleanPose, the first solution to mitigate the confoundering effect in category-level pose estimation via causal learning and knowledge distillation. You can generate the ...
IEEE

Local Causal Discovery with Background Knowledge

Abstract: Causality plays a pivotal role in various fields of study. Based on the framework of causal graphical models, previous works have proposed identifying whether a variable is a cause or ...