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Clinical Decision Support Platform for Early Deterioration Detection

Clinical Decision Support Platform for Early Deterioration Detection

Health
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We built a clinical decision support platform that consolidates patient signals into an operational view for early detection of deterioration. The system ingests vital…

Real-time Health Dashboard with Wearable Sensors

Real-time Health Dashboard with Wearable Sensors

Health
Show project

We built a real-time health monitoring dashboard powered by our proprietary wearable sensor platform and AI algorithms, designed for continuous patient observation in hospitals,…

Health

Clinical Decision Support Platform for Early Deterioration Detection

We built a clinical decision support platform that consolidates patient signals into an operational view for early detection of deterioration. The system ingests vital…

  • Strategy

    Unify bedside, lab, medication, and narrative signals into patient timelines, then apply context-aware risk modelling and explainable prioritisation to reduce missed deterioration and accelerate escalation.

  • Design

    Clinical data ingestion and harmonisation into a secure lakehouse, AI services for forecasting and anomaly detection with NLP enrichment, and clinician-facing workflows for prioritised review, validation, and escalation tracking.

  • Client

    Healthcare providers and hospital networks in the EU.

  • Tags

    anomaly-detection, clinical, healthcare, nlp

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Health

Real-time Health Dashboard with Wearable Sensors

We built a real-time health monitoring dashboard powered by our proprietary wearable sensor platform and AI algorithms, designed for continuous patient observation in hospitals,…

  • Strategy

    Edge-first digital health architecture, robust wearable sensor integration, AI models for fall and activity detection, clinician-friendly dashboards and support for both hospital and home-care use cases, including offline operation with secure synchronisation.

  • Design

    Wearable sensor app with low-latency streaming to a mobile or gateway device, on-device processing for fall detection and activity classification, flexible sync to a central backend, web dashboard with patient and ward views, alerts and trends, and configurable KPIs for remote patient monitoring.

  • Client

    Hospital in Croatia (EU)

  • Tags

    ai, data lake, iot, real-time processing

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