A systematic review of artificial intelligence models for time-to-event outcome applied in cardiovascular disease risk prediction
Artificial intelligence (AI) based predictive models for early detection of cardiovascular
disease (CVD) risk are increasingly being utilised. However, AI based risk prediction models …
disease (CVD) risk are increasingly being utilised. However, AI based risk prediction models …
Advanced machine learning techniques for cardiovascular disease early detection and diagnosis
NA Baghdadi, SM Farghaly Abdelaliem, A Malki… - Journal of Big Data, 2023 - Springer
The identification and prognosis of the potential for developing Cardiovascular Diseases
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …
Deep Learning and Transfer Learning in Cardiology: A Review of Cardiovascular Disease Prediction Models
GS Kumar, P Kumaresan - IEEE Access, 2024 - ieeexplore.ieee.org
Cardiovascular disorders are the primary cause of death on a global scale. The World
Health Organization report indicates that approximately 18 million people die from CVD …
Health Organization report indicates that approximately 18 million people die from CVD …
Survival models and longitudinal medical events for hospital readmission forecasting
Background The rate of 30-day all-cause hospital readmissions can affect the funding a
hospital receives. An accurate and reliable readmission prediction model could save money …
hospital receives. An accurate and reliable readmission prediction model could save money …
[HTML][HTML] A one-dimensional convolutional neural network-based deep learning approach for predicting cardiovascular diseases
DG Honi, L Szathmary - Informatics in Medicine Unlocked, 2024 - Elsevier
Early detection of cardiovascular diseases (CVDs) is crucial for managing cardiovascular
diseases and improving patient outcomes. Deep neural networks have the potential to …
diseases and improving patient outcomes. Deep neural networks have the potential to …
Survival Prediction Landscape: An In-Depth Systematic Literature Review on Activities, Methods, Tools, Diseases, and Databases
Survival prediction integrates patient-specific molecular information and clinical signatures
to forecast the anticipated time of an event, such as recurrence, death, or disease …
to forecast the anticipated time of an event, such as recurrence, death, or disease …
[HTML][HTML] The centre for health informatics: a novel approach to accelerating the field of health data science
DA Southern, CA Eastwood… - … of Population Data …, 2024 - pmc.ncbi.nlm.nih.gov
Precision Medicine and Precision Public Health are approaches to improve population
health. Achieving these goals requires innovation in health informatics. The Centre for …
health. Achieving these goals requires innovation in health informatics. The Centre for …
Learning Individual Readmission-Free Survival Distributions using Longitudinal Medical Events
SSM Davis - 2023 - era.library.ualberta.ca
The rate of 30-day hospital readmission is a common measurement of hospital quality,
which can affect the funding a hospital receives. Over a quarter of readmissions are …
which can affect the funding a hospital receives. Over a quarter of readmissions are …