Predictive ECG Monitoring with Machine Learning: Detecting Sudden Cardiac Arrest and Assessing Hospitalization Risk

Alappatt, Dona Joy (2025) Predictive ECG Monitoring with Machine Learning: Detecting Sudden Cardiac Arrest and Assessing Hospitalization Risk. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (479kB) | Preview

Abstract

Sudden cardiac arrest (SCA) is associated with approximately one-fifth of all the deaths on Earth therefore, it is a major health concern. Increased levels of survival are not optimal since better first- response measures are established. The SCA nature cannot be predicted, which minimizes the potential of preventive services. Machine learning (ML)- based computational models are considered in this case a plausible and computerized alternative to conventional diagnosis. Mathematical processing of bulk of medical records allows use of sophisticated algorithms and allow identification of trends that have potential to forecast a heart complication. AI and deep learning (ML) are becoming increasingly relevant to each other within the healthcare domain, particularly within the domain of precision medicine, clinical analytics, and diagnostic decision support. In this regard, this project has been proposed as a development of a real time electrocardiographic monitoring system to assess the appropriateness of the patients in hospitals. The overall task is to log acute cardiac arrest incidence, and it will be addressed by relying on the advanced machine-learning models and the progressive signal-processing methods.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Horn, Christian UNSPECIFIED
Uncontrolled Keywords:	Heart Signals; ECG – Electrocardiogram; Machine Learning; sequencing models
Subjects:	R Medicine > Healthcare Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	24 Aug 2026 12:04
Last Modified:	24 Aug 2026 12:04
URI:	https://norma.ncirl.ie/id/eprint/9601

Actions (login required)

View Item