Frequently asked questions

PARIS AI, the Polypharmacy Advanced Risk Intelligence System, is a clinical decision-support suite in three components: PARIS AI Poly for polypharmacy risk, PARIS AI AEP for the prevention of acute events, and PARIS-Ai Rehab for recovery after the acute phase. Together they cover the patient journey from medication risk, through the acute event, to rehabilitation.

The PARIS AI page describes each component.

It is the first product of the AEP component, built for sepsis and critical care. It gives care teams advance warning that a patient is heading for a defining clinical threshold, and evidence of stability when a patient is not, across eight clinical decisions from admission to step-down.

The landing page sets out the need it answers and what it does.

Track-and-trigger charts, sepsis definitions and screening tools classify a patient's current state and fire when a threshold is crossed. PARIS AI is designed to warn before the threshold is crossed, and to sit alongside those instruments rather than replace them. It supplies the forward-looking layer they lack.

It is developed as software as a medical device and is following the regulated route to market authorisation. It is not yet authorised for clinical use. Evaluation with clinical partners proceeds in stages that involve no change to patient care until the final stage.

The observations that hospitals already record in the course of routine care. It requires no new data collection, no new devices and no additional laboratory input. Where it is evaluated, it runs on the partner's own records under the partner's information governance.

The method, the inputs and the validation results are disclosed to clinical partners and to the appropriate authorities under confidentiality agreements. They are not published on this website.

Internal validation is complete and clinical validation with NHS and university partners is under way. The programme moves through retrospective validation on a partner's historical records, shadow-mode evaluation on live data with the output invisible to clinicians, and implementation evaluation once the output is visible.

Use the contact form and choose Partnership. We put a confidentiality agreement in place, share the evidence pack, and agree the stage of evaluation that suits the site. The first two stages involve no patient contact and no change to care.

We share the scale and design of the evidence openly in conversation. Performance results, per variable and per validation approach, are provided under a confidentiality agreement.

Access to historical records for retrospective validation under the partner's own governance, a clinical lead, and the usual information-governance and ethics approvals for the stage concerned. We handle the analysis and the reporting.

Fourteen analytical innovations across four domains: clinical AI and health intelligence, pharmacovigilance and drug safety, financial intelligence and forensics, and economic and fiscal intelligence. The portfolio page lists them.

HealthWalletQR and Fiscal Explorer are on the App Store, and the MERD analysis app series covers agricultural analytics. Links are on the portfolio page.

Yes. Data science, statistical modelling, health technology validation, and iOS and macOS development, from proof of concept to deployed system. Tell us about the project.

A health technology and data science company operating through two registered entities: MDY Analytics Ltd in the United Kingdom and MDY Analytics Limited Company in Ghana. The About page tells the story and the Team page introduces the leadership.

London, at 71-75 Shelton Street, Covent Garden, and Accra, at Tabon Loop, North Ridge.

Through the contact form, or by email to info@mdyanalytics.com. We reply within one working day.

Our privacy policy explains what we collect through this website, why, and how long we keep it.