The increasing incidence of dengue virus (DENV) infections poses significant public health challenges in Bangladesh, demanding advanced forecasting methodologies to guide timely interventions. This study introduces a rigorous multivariate time series...
OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques t...
BACKGROUND/PURPOSE OF THE STUDY: Type 2 diabetes mellitus (T2DM)-one of the fastest globally spreading diseases-is a chronic metabolic disorder characterized by elevated blood glucose levels. It has been suggested that the composition of gut microbio...
PURPOSE: We aim to evaluate various proxy selection methods within the context of high-dimensional propensity score (hdPS) analysis. This study aimed to systematically evaluate and compare the performance of traditional statistical methods and machin...
The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In Korea, the CPI significantly impacts decisions on interest rates, fiscal policy frameworks, and the...
OBJECTIVES: To develop a machine learning model to accurately predict stroke risk based on demographic and clinical data. It also sought to identify the most significant stroke risk factors and determine the optimal machine learning algorithm for str...
In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropri...
BACKGROUND: Quantitatively predicting the progression of Alzheimer's disease (AD) in an individual on a continuous scale, such as the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as oppo...
The journal of trauma and acute care surgery
Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
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