1 citations · 1 across the 1 of their papers we have counts for
4 papers
Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks
Kyle Higgins, Ivan Laponogov, Dennis Veselkov +1
Graph neural networks (GNNs) are increasingly used to model biological systems, yet the reliability of post-hoc explanation methods for recovering meaningful molecular mechanisms r…
PPI-Net connects molecular protein interactions to functional processes in disease
Kyle Higgins, Guadalupe Gonzalez, Dennis Veselkov +2
Understanding how molecular alterations propagate across biological systems to drive disease remains a central challenge. Although high-throughput profiling enables comprehensive c…
The Helicobacter pylori AI-Clinician: Harnessing Artificial Intelligence to Personalize H. pylori Treatment Recommendations
Kyle Higgins, Olga P. Nyssen, Joshua Southern +6
Helicobacter pylori (H. pylori) is the most common carcinogenic pathogen worldwide. Infecting roughly 1 in 2 individuals globally, it is the leading cause of peptic ulcer disease,…
Foundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation
Hamideh Kerdegari, Kyle Higgins, Dennis Veselkov +8
The integration of artificial intelligence (AI) in medical diagnostics represents a significant advancement in managing upper gastrointestinal (GI) cancer, a major cause of global…