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Jul 15, 2019

Current and Future Applications in Artificial Intelligence in Cardiology

AI to Improve Patient Centric Health Care Delivery in Patients Admitted to Cardiology Wards

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Patient Experience

Machine Learning

Artificial Intelligence

Patient Feedback

Impact Factors

Patient Intervention

Abstract

Abstract

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Keywords

Patient Experience

Machine Learning

Artificial Intelligence

Patient Feedback

Impact Factors

Patient Intervention

Abstract

Healthcare sector is utilizing AI to improve patient health care delivery process efficiencies. We have utilized machine leaning (ML) XGBoost model to capture patient experience in real-time during their stay in cardiac ward. This ML model predicts patient experience while the patient is still in the hospital so the concerns of the patient and the family can be addressed during the hospital stay. ML model identifies patterns that predict patient experience (PE) score. When a low PE score is predicted, Patient Experience Intervention Framework (PXIF) generates an Intervention plan. This plan is assigned to the relevant staff members with specific tasks to improve the patient’s experience. With PXIF medical team was able to intervene before the patient is discharged.

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© Copyright 2019 Morressier GmbH. All rights reserved.

© Copyright 2019 Morressier GmbH.
All rights reserved.