iheallab/apricotM
This repository contains the official code for the paper "Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling" (Nature Communications), which presents a deep learning framework for real-time patient acuity prediction using EHR data.
This project helps critical care teams predict real-time patient acuity and therapy needs in the ICU by analyzing electronic health record (EHR) data. You input a patient's historical EHR data, and it outputs continuous predictions of their stability and potential need for interventions. ICU clinicians, nurses, and hospital administrators can use this to anticipate changes in patient condition and allocate resources proactively.
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Use this if you need to build or evaluate a system for real-time, continuous prediction of patient deterioration and therapy requirements within an Intensive Care Unit using historical EHR data.
Not ideal if you lack access to large, granular Electronic Health Record (EHR) datasets from ICU patients, or if your primary need is not real-time acuity prediction.
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Jul 22, 2025
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