Trust in healthcare is not assumed; it must be calculated and proven. Historically, "black box" skepticism has hindered AI adoption.
LoomClinical deploys AI models as real-time web applications, utilizing SHAP and LIME frameworks to provide immediate, mathematically sound interpretability. Clinicians instantly understand exactly why a recommendation is made, ensuring absolute clinical trust.
The Clinical Safety Hub is a live, AI-powered decision support platform engineered to prevent fatal drug-drug interactions (DDIs) before a prescription is ever filled.
Built on advanced Graph Neural Network (GNN) architecture, the platform models highly complex, non-linear medication profiles, instantly providing actionable safety alerts directly into existing clinical workflows.
We are bridging the critical research gap in AI-assisted optimization for combination therapies, focusing our application on the most complex prescribing environments in modern medicine.
HIV-TB pathogenesis requires highly complex multi-drug regimens. Our platform maps the severe pharmacokinetic interactions between antiretrovirals (ART) and rifamycin-based TB therapies, preventing life-threatening toxicities.
Our Clinical Safety Hub operates specialized, production-ready HIV drug interaction algorithms. This isn't theoretical; it is backed by documented patient cases and successfully integrated into active clinical workflows.
Managing diabetes alongside infectious diseases significantly increases DDI risk. The Graph Neural Network analyzes the full patient profile—identifying obscure, compounding interactions that traditional linear databases miss entirely.