About CogStack

Centralise and lake clinical data including structured data i.e. observations, results, and unstructured data i.e. clinical narratives such as clinic letters, discharge and admission summaries and radiology reports also varying formats e.g. binary word docs, PDFs, images.

Search and visualise millions of distinct data points in near-real-time – ‘unlocking’ capabilities that would otherwise have taken days or months previously.

Natural Language Processing of clinical text to standardised clinical terminologies (SNOMED-CT) for interoperable clinical data combined with semantic context. This allows cohorting based on “find all patients with a heart attack”, regardless of how this has been referred to in the clinical text, such as “patient had myocardial infarct”, “MI“, “infarct of heart”, “cardiac infarct” and distinguishing “the patient’s father had a MI”.

Deep phenotyping using NLP allows accelerated NHS clinical coding, disease registry submissions and advanced cohorting for observational studies.

Population health dashboards for combining data from structured and text components of the electronic health record to track patient outcomes, enhance patient safety and improve patient care.

Advanced analytics using generative AI for virtual trial emulation, high-dimensional patient or disease modelling and digital patient twins.