Frontiers

Beyond the Algorithm: Scalable, Explainable, and Adaptive AI for High-Stakes Clinical Decision Support

Artificial Intelligence (AI) has shown strong potential in supporting clinical decision-making through Clinical Decision Support Systems (CDSSs). However, ...
OECD

Using digital resources for learning

Standards and guidelines for development co-operation with concrete examples of their implementation ...
Santa Clara University

Beyond Explainability: The Ethical Imperative for Validated and Interpretable Clinical AI

Evan Hackstadt is a computer science major with minors in biology and math. He is a 2025-26 health care ethics intern at the Markkula Center for Applied Ethics at Santa Clara University. Views are his ...
Microsoft

HypeMed: Enhancing Medication Recommendations with Hypergraph-Based Patient Relationships

Medication recommendations aim to generate safe and effective medication sets from health records. However, accurately recommending medications hinges on inferring a patient’s latent clinical ...
IEEE

Fairness-aware Hypergraph Self-Supervised Learning with Sampling-efficient Signals

Abstract: Self-supervised learning (SSL) provides a promising paradigm for hypergraph representation learning without reliance on costly labels. However, existing hypergraph SSL methods predominantly ...
IEEE

HHGSynergy: An Adaptive Heterogeneous Hypergraph Representation Learning Method for Anticancer Drug Synergy Prediction

Abstract: Compared with monotherapy, combination drug therapy plays a crucial role in clinical treatment. However, the exponential expansion of the drug combination space has rendered traditional ...