Nature

Knowledge graph-aided Bayesian active learning for top-K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the ...
Nature

Knowledge-graph embeddings for osteoarthritis candidate prediction

Osteoarthritis (OA) is a prevalent, disabling joint disease with no approved disease modifying treatments. We present a knowledge-graph based approach to discover candidate treatments for OA by ...
ascopubs.org

Machine Learning–Assisted Recurrence Prediction for Patients With Early-Stage Non–Small-Cell Lung Cancer

For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...
Search Engine Land

Google’s great clarity cleanup: 3 shifts redefining the Knowledge Graph and its AI future

Billions of entities vanished from Google’s Knowledge Graph in June 2025. Here’s how it signals a bold new direction in AI-powered search. Google’s Knowledge Graph saw its largest contraction in a ...