Evidence in life sciences & healthcare.
Diagnostic and clinical-support applications of Agxio’s platform, benchmarked and built for explainability — labelled by its actual evidence status.
Multimodal healthcare classification
83% accuracy and a 0.96 ROC AUC on a labelled, multi-class brain-MRI benchmark, demonstrated by Agxio as in line with specialist-level performance. Agxio⋅Intelligence built and validated the multimodal classification models directly from imaging data, while Agxio⋅Cognition generated the clinician-facing, source-traceable explanation behind every classification.
Explainable AI for skin cancer screening
An explainable prediction engine covering the top 20 skin cancer conditions — around 95% of all presenting cases. Agxio⋅Intelligence builds the underlying discriminative and generative classification models directly from clinical imaging, and Agxio⋅Cognition combines those with rules-based reasoning to produce clinician-interpretable, source-traceable output.
End-of-life pathway & COVID causal-factor analysis
Agxio developed a machine learning solution to identify end-of-life care pathways and the critical causal factors associated with COVID-19 outcomes, working across structured clinical records and unstructured case notes to surface the variables that mattered most. Agxio⋅Intelligence built the underlying causal and survival-modelling pipeline directly from patient-level data, while Agxio⋅Cognition turned model output into source-traceable, clinician-reviewable narrative rather than an opaque risk score.
Bionanotechnology framework for Johne’s disease
Agxio developed a bionanotechnology beta framework to address Johne’s disease in animals — a chronic, hard-to-detect mycobacterial infection with major herd-health and economic impact. Agxio⋅Intelligence models the relationship between nanotechnology-derived biomarker signals and infection stage, while Agxio⋅Cognition turns those signals into a defensible, review-ready diagnostic read-out.
Live patient data analysis for care analytics
Agxio analyses live patient data to power care analytics — surfacing risk, trajectory and intervention signals directly from real-time clinical data streams rather than retrospective reporting. Agxio⋅Intelligence builds the underlying predictive models from live patient-level data, and Agxio⋅Cognition delivers source-traceable, clinician-ready output at the point of care.
We label every result by its actual status — historical demonstration, completed programme, pilot or evaluation, beta, product capability, or live deployment — and update labels as work progresses. We do not present a benchmark result as a production outcome, a beta as a finished product, or a pilot as a deployment.
Want the detail behind a result?
We’re glad to walk through methodology, data provenance and evaluation design for any case here.
Discuss a high-value use case