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Diagnosis of Coronary Artery Disease based on Machine Learning algorithms Support Vector Machine, Artificial Neural Network, and Random Forest
CONCLUSION: In this study, it was shown that machine learning algorithms can be used with high accuracy to detect CAD. Thus, it allows physicians to perform timely preventive treatment in patients with CAD.PMID:37057235 | PMC:PMC10086656 | DOI:10.4103/abr.abr_383_21
Source: Adv Data - April 14, 2023 Category: Epidemiology Authors: Saeed Saeedbakhsh Mohammad Sattari Maryam Mohammadi Jamshid Najafian Farzaneh Mohammadi Source Type: research

Characteristics and predictors of hospitalization and death in the first 11  122 cases with a positive RT-PCR test for SARS-CoV-2 in Denmark: a nationwide cohort
ConclusionsIn this nationwide population-based COVID-19 study, increasing age and multimorbidity were strongly associated with hospitalization and death. In the absence of co-morbidities, the mortality was, however,<5% until the age of 80  years.
Source: International Journal of Epidemiology - September 5, 2020 Category: Epidemiology Source Type: research

Cardiovascular Disease Treatment Outcomes in Patients with Diabetes: Prediction Models Using Artificial Neural Networks and Logistic Regression
Diabetes mellitus (DM) is not only a major risk factor for coronary heart disease (CHD); it also worsens CHD prognosis. The study's purpose was to investigate comparative effectiveness of two major CHD treatment procedures - coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) - in a population of CHD patients with DM (CHD-DM), using an artificial intelligence tool - artificial neural networks (ANN) - and a traditional multivariable logistic regression (MLR).
Source: Annals of Epidemiology - August 21, 2015 Category: Epidemiology Authors: Alexander V. Sergeev, Gary R. Weckman Tags: Cardiovascular Diseases and Stroke Source Type: research