AI-Driven Solutions for Healthcare Data
We apply cutting-edge artificial intelligence and machine learning techniques to healthcare data, including GP records, hospital data, and international claims datasets, delivering validated, explainable models that support clinical decision-making, operational efficiency and research.
What We Do
- Develop supervised and unsupervised machine learning models on primary and secondary care data
- Apply Natural Language Processing (NLP) to clinical text, including GP notes and discharge summaries
- Build and deploy Large Language Model (LLM) solutions for healthcare
- Create explainable AI (XAI) tools for clinical settings
- Develop predictive models using linked GP and HES data
- Integrate RCT and real-world data for hybrid evidence generation
Data Sources We Apply AI To
- GP records: primary care clinical text and structured data from EMIS, SystmOne and Vision
- Hospital Episode Statistics (HES): secondary care data for outcome prediction and pathway modelling
- Linked primary and secondary care data: for longitudinal AI model development
- CPRD Aurum & Gold: research-grade data for model training and validation
- US and EU health data: for international AI applications
- Clinical trial datasets: integrated with real-world data for complete evidence
Use Cases
- Early disease detection and risk scoring from GP data
- Hospital readmission and length of stay prediction using HES
- Clinical note summarisation using LLMs
- Automated medical coding and phenotyping
- Population health risk stratification
- Multimorbidity pattern identification
What You Get
- Validated, explainable AI models
- NLP pipelines for unstructured clinical data
- LLM-powered clinical tools
- Models trained on linked primary and secondary care data
- Fully documented, reproducible methodology