Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...
Guzmán, P. and Halpern, M. (2026) Effects of Treatment Delays on Colorectal Cancer Survival. Journal of Cancer Therapy, 17, ...
Background The long-term trajectories of estimated glomerular filtration rate (eGFR) and their relation to early proteinuria ...
Medicaid is the largest payer of substance use disorder treatment in the US, 8 covering approximately 38 percent of nonelderly adults with OUD as of 2019. 9 The Substance Use Disorder Prevention that ...
Abstract: Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings ...
1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Objective: To develop and validate a logistic regression model predicting postoperative malnutrition risk in elderly patients using clinical, dietary, and nutritional data. Table 1. Comparison of ...
Abstract: Outsourcing logistic regression classification services to the cloud is highly beneficial for streaming data. However, it raises critical privacy concerns for the input data and the training ...
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