Country / Region
EMEA
Tags
Artificial intelligence, Data analytics, Patient safety, Research
Chronic Kidney Disease (CKD) is a progressive condition that often goes undiagnosed until it reaches advanced stages, necessitating dialysis or kidney transplantation. Late presentation of CKD, particularly when dialysis is imminently required, significantly worsens patient outcomes and increases healthcare costs. This research proposal aims to develop and validate an artificial intelligence (AI)-based model to identify patients at high risk of late presentation of CKD, thereby enabling timely interventions and improving clinical outcomes.
Description
An AI-Tool can be created and integrated into patient pathways, utilising SNOMED CT, to identify and predict risk of late presentation of Chronic Kidney Disease.
Scope
SNOMED CT was selected due to it's structured and coded vocabulary, it provides a backbone for identifying conditions as a part of an NLP Model.
How SNOMED CT will be used
SNOMED CT was used in a Natural Language Processing model to help identify comorbidities from patient's electronic health record
Why SNOMED CT will be used
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